tourism on metaverse

Tourism in the metaverse: Can travel go virtual?

Imagine a future where your travel choices have no geographic constraints. Where you can join your friends in the front row of a concert by your favorite star—but the crowd is 300 million strong, your friends are on the other side of the world, and it’s all happening at the Great Pyramid of Giza. Later you’ll do some shopping at the virtual souk and take a digital Nile cruise, before teleporting back home in an instant.

Impossible? Or a tempting package trip that might soon be available from the comfort of your home? With the internet’s rapid evolution, many see this vision of transformed travel on the horizon—in the metaverse. Others caution that this future might take a little longer to arrive, and that travelers resist “metaversification” of key parts of the tourism journey.

The metaverse is seen as the next evolution of the internet—a collective space where physical and digital worlds converge to deliver more immersive, interactive virtual- or augmented-reality (VR/AR) user experiences, often referred to together as extended reality (XR). The underlying technology for this exists and is proving relatively cheap and fast to implement. Driven largely by inspirational advertising and virtual events, the potential rewards for the travel industry are already substantial: more than $20 billion by 2030, by McKinsey estimates.

This has potential to revolutionize the way we explore new worlds: already, you can attend concerts, shop, test products, visit attractions, and take workshops, all without physically traveling anywhere. Currently, the user demographic trends very young, but it’s crucial for the tourism sector to appeal to this segment. 1 Hristina Nikolovska, “Metaverse Statistics to Prepare You for the Future,” February 16, 2023. After all, these are the travelers of the future—and players not keeping pace with their interests will lose out.

But does XR live up to all the hype—with appeal beyond a gamer demographic? A virtual trip can never replace the thrill of certain tangible, real-word experiences, and some traveler touchpoints have proved more ripe for disruption than others.

Despite these hesitations, the XR ecosystem is maturing at pace. Immersive VR/AR devices may well follow the steep adoption curves of laptops and smartphones. Widespread use could lead to a radical extension of the global economy from physical into virtual life, not least in tourism.

So how does a tourism player go about monetizing this virtual paradigm, which is still taking shape and many struggle to define? It’s time for the sector to take a serious look at these complex opportunities—and figure out what best drives traction in the new XR universe.

Touring the metaverse: early trends

The metaverse could enrich the tourism experience in countless unprecedented, innovative ways—but which use cases have the most potential, and which are still deemed risky? Early adopters have already started experimenting, and several trends have emerged. Virtual elements can be layered onto an established business:

• In the wake of the fire that damaged the famous cathedral in 2019, French start-up Histovery produced an augmented exhibition on the history of Notre-Dame de Paris—motivated in part by an increased awareness of the fragility of physical landmarks. To navigate the exhibition, each visitor uses a “HistoPad” touch screen to take an immersive tour that allows interaction with physical elements: giant photographs, 3-D models of statues, replica flooring and stained glass, and audio of Notre-Dame’s organs and bells. Effects include animation and a virtual scavenger hunt for younger visitors. 2 “Notre-Dame de Paris: The Augmented Exhibition,” National Building Museum, April 2022.
• In December 2021, faced with record staff turnover, MGM Resorts International decided to apply a virtual solution. In partnership with immersive platform provider Strivr, MGM developed VR headsets that give aspirant front-of-house staff a realistic sense of what working at MGM casinos and hotels entails. The training package was rolled out at the company’s properties in 2022. It’s designed to speed up onboarding and upskilling, increase employee confidence, and familiarize potential hires with MGM procedures and culture. 3 Grace Dean, “MGM Resorts is letting job seekers try out roles using virtual reality as it looks to reduce employee churn,” Business Insider, December 12, 2021; Phil Albinus, “Rising Star goes all in on VR talent marketplace for MGM Resorts,” Human Resource Executive, June 14, 2022; “4 Examples of Strivr Virtual Reality Training,” Strivr.com.

Other virtual platforms allow visitors to explore major global landmarks, incorporating rich edutainment and retail opportunities. Several such initiatives have been launched:

• Responding to pandemic travel restrictions, ZEPETO World is a smartphone app that allows users to create personal avatars and travel around Korea. For example, the tour includes a highly detailed interactive map of Han River Park; this feature gets almost 257,000 visitors a day. Users are also able to communicate with each other, shop, and watch performances. ZEPETO World has approximately 190 million members. 4 Majid Mushtaq, “Korea Virtual Travel with ZEPETO World,” KoreabyMe, September 6, 2021.
• The BCB Group—a leading crypto banking group—has created a metaverse city that includes representations of some of the most visited destinations in the world, such as the Great Wall of China and the Statue of Liberty. According to BCB, the total cost of flights, transfers, and entry for all these landmarks would come to $7,600—while a virtual trip would cost just over $2. 5 “What impact can the Metaverse have on the travel industry?” Middle East Economy , July 29, 2022.
• Saudi Arabia’s Royal Commission for AlUla (RCU) recently announced that the ancient city of Hegra had entered the metaverse, in line with a national program to drive technological transformation and innovation. It is the first UNESCO World Heritage Site to be placed in the metaverse, allowing digital tourists to explore the surroundings as well as Hegra’s Tomb of Lihyan son of Kuza. 6 Divsha Bhat, “Saudi’s Royal Commission for AlUla enters the metaverse,” Gulf Business , November 15, 2022; “Vision 2030,” The Embassy of the Kingdom of Saudi Arabia; “Saudi Arabia’s AlUla enters the metaverse,” Arabian Business , November 14, 2022; One Carlo Diaz, “Hegra’s Tomb of Lihyan in AlUla is recreated in the metaverse,” NTravel, November 7, 2022.

Instead of attempting to replicate real-world experiences, entirely novel environments can also be created, convening people in a single immersive space—as in multiplayer online games. (Indeed, many people currently associate the metaverse largely with games.) The travel industry can harness this utility too.

This is particularly relevant to the meeting, incentives, conferences, and exhibitions (MICE) sector, with virtual gatherings, exhibitions, and trade fairs looking to become mainstream. These allow people to gather and take part in activities in the same immersive space, while connecting from anywhere. This dramatically reduces travel, venue, catering, and other costs, while avoiding setbacks like adverse weather conditions or disease scares. For example, one Japanese start-up recently held a virtual market that attracted a wide response, with around 60 well-known companies participating. 7 “Metaverse x MICE; 3D virtual world that will transform MICE industry in the future,” Thailand Convention and Exhibition Bureau.

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What areas of tourism show promise.

As innovative formats become more mainstream, new economic models are emerging. The travel experience of the future will not be exclusively online or offline. Instead, we’ll most likely see a proliferation of hybrid offerings, with virtual events, edutainment, and inspiration combined with physical destinations.

One way to grapple with this complexity is to adopt a traveler-first mindset. By putting themselves in the shoes (or bedroom slippers) of their target tourist, travel companies can identify opportunities to embed relevant virtual elements.

Individual touchpoints, not end-to-end offerings

Virtual experiences that show promise are focused on a few specific, discrete steps in the end-to-end traveler journey (exhibit). Which touchpoints can be most effectively disrupted? Which hold the greatest possibilities for integration? Which steps can be elevated by an immersive element, allowing for exhilarating, fantastical or deluxe experiences not available in the physical world? Three touchpoints show great potential: travel inspiration, virtual events and visitor support.

Inspiration and planning: The metaverse creates a $13 billion opportunity for tourism inspiration, mostly driven by digital travel advertising. Virtual spaces—which can be used to showcase hotel amenities, airline classes, or an entire landmark—spark the desire to travel, give a holistic idea of a destination, help in traveler decision-making, showcase broader offerings, and raise awareness of unfamiliar locations. The case studies of AlUla and ZEPETO demonstrate how this can work. Qatar Airways offers another example: a recently launched VR experience called QVerse allows travelers to view cabin interiors, the business-class QSuite, and the VIP check-in area at Hamad International Airport. 8 Rose Dykins, “Qatar Airways creates virtual reality ‘QVerse’ experience,” Globetrender, June 13, 2022.

Leisure and entertainment: Live streaming soared during the pandemic, followed by a wave of interest in virtual concerts—with significant increases in consumer demand, spend, and audience numbers. 9 John Koetsier, “Virtual Events Up 1000% Since COVID-19, With 52,000 On Just One Platform,” May 27, 2020. In 2020, the metaverse accounted for 0.1 percent of live-music revenues—a figure which rose more than tenfold by 2021. By 2030, we estimate that virtual events could account for up to 20 percent of revenues, driven in part by their capacity to accommodate huge audience numbers at reduced cost.

Ariana Grande leads the way into the music future

In August 2021, Epic Games launched its latest Fortnite event, the Rift Tour, starring Grammy-winning artist Ariana Grande. 1 Isamu Nishijima, “Ariana Grande x Fortnite Rift Tour: The Apogee of Pop Culture or Just the Beginning?”, Headline Asia Publication , Aug 30, 2021. It was a match made in heaven: Fortnite, a wildly popular battle-royale game with then around 350 million registered users, and Ariana Grande, a universally adored pop artist. 2 Emi La Capra, “The Metaverse Concerts: Where Online Games and Music Performances Meet,” Alexandria , 2022. One of the first of such Fortnite collaborations, this was particularly significant: the first time Ariana Grande had performed in nearly two years, and the first concert to allow attendees to participate in minigames.

The concert was an acclaimed success. The Rift Tour was viewed by as many as 78 million players (compared to average conventional concert attendance of under 15,000); the number of streams of Grande’s songs rose by up to 123 percent during the concert, and other featured artists also saw a streaming boost. 3 Maggie Klaers, “PCP: Concert attendance,” SLP Echo, April 29, 2022. While a traditional concert by a top North American performer might rake in less than $1 million, it’s estimated that Grande made more than $20 million from her headline performance—which may be remembered as a critical inflection point for the live-entertainment industry. 4 Bob Allen, “Concert Industry Roars Back! Pollstar 2022 Mid-Year Report,” Pollstar, June 24, 2022.

With top artists generating around $20 million per metaverse concert, this industry has an anticipated income potential of upwards of $800 million by 2025, according to McKinsey estimates (see sidebar, “Ariana Grande leads the way into the music future”). Taken together with XR MICE, this sector is a rich opportunity: an expected $7 billion by 2030.

Visitor support: Some destinations have been exploring the idea of virtual concierges to support travelers at every stage of the journey with real-time itineraries, information, troubleshooting, visa issues, and more. Qatar Airways, for example, provides a MetaHuman cabin crew for an interactive customer experience. Immersive use cases already account for over 1 percent of chatbot investment, and this is expected to increase. Still, it may be several years before this touchpoint gains real traction.

Then there are touchpoints where the disruption potential of the metaverse is still debatable, or where opportunities may take longer to mature:

• Shopping: Multiple stores could be built in virtual destinations, adding a revenue stream with the sale of accessories, souvenirs and other items. These might be digital, or goods to be shipped in the real world. Iconic real-life stores might also operate as digital recreations.
• Booking: Customers are already comfortable with online booking, so a shift to XR interactions with virtual travel agents could be seamless. However, this is a relatively small business opportunity, with uncertain added value: the new technology is not expected to change or boost the functionality of current booking processes in any fundamental way.

There is currently limited interest in adding virtual elements to aspects of travel that are necessarily physical, such as mobility, accommodation, the logistics of arrival and departure, and food and drink (F&B).

Mobility is currently expected to have very limited XR use cases: tourists may access a metaverse experience while in a taxi, but are unlikely to replace physical with virtual mobility. The “stay” category is similarly sized. While people may wish to explore virtual stays in hotels or on cruise ships, these will not yet replace actual stays. Hotel developer CitizenM, for example, has announced plans to build a hotel in gaming world The Sandbox, allowing virtual visitors to explore the digital property and raise awareness of its brand. 10 Cajsa Carlson, “CitizenM to become ‘first hospitality company to build in the metaverse’,” dezeen, April 7, 2022.

Similarly, arrival-and-departure use cases are largely limited to customers seeking XR versions of modes of transport, such as business-class flights or special railway routes, without intending to visit. (Such experiences may serve as “portals” to expanded immersive worlds, however.) The F&B industry will likely be among the last to enter the metaverse.

Post trip, the real potential lies in the capacity to inspire further travel. However, actual follow up, currently often achieved via surveys, is unlikely to be deeply impacted.

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“no-regret” metaverse moves.

Taking the above factors into account, there are certain no-regret functions that tourism-industry players can pursue to be at the forefront of disruption. These promising use cases have already gained traction, with fast-moving industry players stepping in early to bet on their viability.

They fall into two categories: virtual event centers, and recreations of memorable landmarks that inspire visits. As we’ve seen, event centers are already showing substantial revenue potential for organizers and destinations through business gatherings and entertainment, with ticket sales, attendance fees, and ancillary retail opportunities.

At XR landmarks, visitors can explore, socialize, shop, and learn—all while gaining awareness of lesser-known destinations. Young people and tourists may flock to these social spaces for immersive fun. There may be edutainment opportunities, including specialized archaeology, geology or architecture classes. These spaces can be built on established or upcoming platforms (such as Metapolis) and operate in collaboration with third-party vendors to increase retail opportunities.

Themed gaming, too, can drive engagement with a location, and caters to a core XR demographic. This includes game developers: Unreal Editor for Fortnite (UEFN) is a newly released PC application for designing and publishing games and experiences directly into the online video game Fortnite. 11 The Fortnite Team, “Unreal Editor for Fortnite and Creator Economy 2.0 are here. New worlds await,” Fortnite, March 22, 2023.

There appears to be public appetite for recreations of individual landmarks rather than entire destinations: a metaverse Eiffel Tower rather than a complete metaverse Paris. An example is Dubai’s Burj Khalifa virtual experience, launched by event-management platform Eventcombo, which offers users a focused tour of the world’s tallest building. 12 “Dubai: Take an immersive tour of Burj Khalifa in metaverse,” Khaleej Times, October 8, 2022. For now, there seem to be fewer opportunities to create whole customer journeys (although this may work well for certain cases like theme parks). When it comes to end-to-end tourism experiences, travelers still seem prefer the “real thing.”

Preparing for the future of travel

How can travel companies leverage the metaverse to create more compelling experiences for their customers? Certain challenges must be overcome: these include enabling interoperability between decentralized worlds, protecting data security, and making immersive devices more readily available.

However, it’s prudent for travel players to think proactively about engaging with the metaverse—and perhaps seize a first-mover’s advantage. Early control will help to sidestep thorny issues like third parties claiming virtual rights to a location.

Once travel players have plotted out potential traveler journeys (whether hybrid or fully digital), they can find the right collaborators to bring these experiences to life—such as virtual-universe and retail platforms, communications channels, and designers. As many tech players are still only starting to come to grips with immersive experiences, companies may be able to secure favorable partnership agreements and experiment with different executions.

Four steps for travel players contemplating the metaverse

Step 1: Create a strategy based on individual traveler touchpoints to be disrupted. Develop offers targeted at travelers of the future, considering demographic groups, travel purpose and likely journeys. Imagining specific future touchpoint needs and desires and how these can be satisfied or enhanced in a virtual world will ensure a targeted strategy.

Step 2: Identify the platform you want to play on. There are several options here, depending on factors like the strength of your brand and how much independence you require. With a very strong brand, you might be in a position to create your own platform. If your brand is less widely recognized—as with most tourism destinations—or the advantages of a dedicated platform are not clear, then it might be unwise to go it alone. It may be possible to integrate your experience with another organization’s platform, with the added benefit that their established users can stumble across your product. Or partner with an existing platform, as Saudi Arabia’s RCU have done with browser-based platform Decentraland and Korean tourism with the ZEPETO app.

Step 3: Choose the right talent. Developing any offer will likely require new skills—not just to make your immersive world look good, but to ensure that it’s smooth and exhilarating to use. Excellent “game mechanics” motivate users to come back repeatedly for new experiences. In turn, this requires constant maintenance, operation and innovation, as with any great tourist attraction. Talent for these tasks can be either recruited or outsourced. Hiring a new, dedicated workforce might make sense for a large service that requires intensive modification and security monitoring. For simpler or once-off offerings developed to test the waters, outsourcing will ensure a smoother, faster process.

Step 4: Understand the agreement you have with your partner. Be sure to clarify safeguards related to IP and other potential challenges. Also ensure that virtual experiences cohere with your existing brand identity, as well as the values and cultural context of heritage assets.

The metaverse promises to shake up many sectors of the global economy. Virtual experiences have huge potential for the tourism and travel industries, with the prospect of hybrid and fully immersive digital destinations. But our research indicates that opportunities may, for now, be limited to a few key touchpoints—most prominently, travel inspiration, events, and edutainment. It may take longer for the metaverse to reveal its utility for end-to-end travel experiences, if it ever does.

Nonetheless, there are undeniably travel touchpoints where metaverse integration feels inevitable, profitable and “no regret.” Players in the sector would do well to start planning their metaverse strategy now, focusing on specific touchpoints and destinations, while this rapidly developing arena matures.

Margaux Constantin is a partner in McKinsey’s Dubai office, where Kashiff Munawar is an expert associate partner; Giuseppe Genovese is a consultant in the Dallas office; and Rebecca Stone is a consultant in New York City.

The authors wish to thank Samvit Kanoria, Hamza Khan, and Kevin Neher for their contributions to this article.

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Doctorante en sciences de l'information et de la communication, rattachée au laboratoire Dicen-IdF. Tourisme et Smart Tourisme, Université Gustave Eiffel

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Naïma Aïdi does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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The metaverse can be defined as a set of virtual shared spaces that are indexed in the real world and accessible via 3D interaction. It is a term that has been rapidly gaining ground in the media landscape ever since Facebook founder Mark Zuckerberg announced the creation of the Meta Group.

While some people remain cautious or resistant to the idea, others see this technological evolution as an opportunity to develop new offers. Given tourism is a sector that moves forward largely in line with information and communication technologies, it is entirely relevant to look at how it could integrate this virtual universe.

So how could the metaverse take over tourism, a practice that requires physical travel?

Can tourism and technology work together?

There is a clear correlation between the development of tourism and that of technology. Indeed, from the computerised booking centres of the 1970s to the domestication of the Internet in the late 1990s, technology has always been used in tourism to develop new practices . The metaverse is part of this evolution of the Internet, which deploys increasingly immersive technologies to offer phygital experiences – i.e., that blur boundaries between the real and the virtual.

Whether it be for museums, national parks or heritage sites, the health crisis has also enabled many organisations to increase and sustain their use of technological tools to offer virtual reality tours. The Fly Over Zone application, as well as offering an exploration of World Heritage cultural sites, shows users what damaged sites would have looked like in their original state. Web giant Amazon launched “Amazon Explore” , allowing people to “travel the world, virtually”. This venture is an interactive live-streaming service, which they say allows you to discover new places from your computer. Although this service is still in its infancy, with a beta version it is likely that these virtual tours will progress to offer even more immersive formats.

When it comes to tourism, Asia is a forerunner, with proposals such as the Seoul Metaverse project, which aims to become the first major city in the world to enter the metaverse, with a tourist route reproducing the city’s main sites. But it is in France that we find one of the most successful projects with MoyaLand , a virtual tourism realm including a tourist office, museums, an airport and a historical centre where inhabitants and tourists can move around virtually via their avatars.

Other tourism stakeholders could follow suit, with 25% of people forecast to spend at least one hour a day in the metaverse by 2026, according to the American company Gartner . So how will people experience tourism in this virtual environment?

Using the metaverse to inspire travel

There are two main trends defining the tourism experience : the first is related to the process, with a transformation of the world into knowledge, the second is about the moment, with a focus on hedonism and feelings of success. While by definition, tourism requires physical travel, there is a contradiction in the tourism experiences offered by the metaverse. The metaverse cannot replace physical travel, but can create the desire to travel.

In the immersive reality of the metaverse, technological devices feed the user with sensations such as sight, hearing, touch and even smell. Besides acquisition costs, the use of these new devices calls into question the perception of the senses connecting humans to their environment.

The metaverse results from the interaction between a device, a user putting themselves in the shoes of a tourist, and other spectators. Although the experience is virtual, the senses are indeed put to work by stimulating certain situations that are desired but not accessible at the time. Through immersion, the virtual reality headset or haptic sensors allow us to experience things that were previously intangible and to reconnect with the senses. Through an avatar, the metaverse user can embody a tourist by creating a virtual tour route, interacting with other avatars and consequently imagining how they feel, stimulating what Giacomo Rizzolatti calls mirror neurons .

Societal and environmental constraints

Whether imitated, reproduced or simulated, travel and holidays are touristic practices that provide a break from everyday life. They’re also an opportunity for some to see their loved ones or to engage in activities that are difficult to do in everyday life. Observing animals in a safari, discovering archaeological sites or practising a foreign language are activities that produce unique, essential bodily and spiritual sensations different from those produced virtually by metaverse devices.

Moreover, the metaverse, which is in itself a technological development of the Internet, is not yet complete. It requires financial investment and the construction of a regulatory framework to control user behaviour. For when Mark Zuckerberg expresses his desire to create a virtual and alternative world in which users can also travel, we must not lose sight of the fact that users’ data will be put to use. And while some people see the metaverse as a solution to avoid flying and move toward sustainable tourism, the digital pollution it will create could well work against this ‘virtuous’ form of tourism.

Although tourism in the metaverse will not be able to replace outdoor experiences, some tourism professionals could use it to promote sites that are not easily accessible or are ignored by tourists, who can discover them virtually.

This article was originally published in French

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Distribution of travel and tourism spending in Europe in 2019 and 2023, by type

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Distribution of travel and tourism spending in Italy in 2019 and 2023, by type of tourist

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Total contribution of travel and tourism to employment in Belgium in 2019 and 2023, with a forecast for 2024 and 2034 (in 1,000 jobs)

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Tourism in the metaverse: Can travel go virtual?

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Imagine a future where your travel choices have no geographic constraints. Where you can join your friends in the front row of a concert by your favorite star—but the crowd is 300 million strong, your friends are on the other side of the world, and it’s all happening at the Great Pyramid of Giza. Later you’ll do some shopping at the virtual souk and take a digital Nile cruise, before teleporting back home in an instant.

Impossible? Or a tempting package trip that might soon be available from the comfort of your home? With the internet’s rapid evolution, many see this vision of transformed travel on the horizon—in the metaverse. Others caution that this future might take a little longer to arrive, and that travelers resist…

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Please note you do not have access to teaching notes, metaverse tourism for sustainable tourism development: tourism agenda 2030.

Tourism Review

ISSN : 1660-5373

Article publication date: 8 November 2022

Issue publication date: 7 April 2023

The purpose of this study is to define metaverse tourism and to provide a viewpoint and further research regarding metaverse tourism with respect to its potential for sustainable tourism.

Design/methodology/approach

This study investigated the potential of the metaverse for sustainable tourism based on United Nations World Tourism Organization (UNWTO) reports, Google Trends data and previous studies including human–computer interactions, virtual reality and cognitive studies.

This research found that metaverse products and experiences could aid in expanding the range of tourism resources and support sustainable tourism by providing alternative and profitable resources. Producing licensed and profitable metaverse tourism products and experiences could increase profitability for tourism destinations and should be developed in accordance with the UNWTO Sustainable Development Goals (SDGs).

Research limitations/implications

Using metaverse tourism products and experiences is a new approach to attain the SDGs. Analysis of accumulated data from further empirical studies and case studies is necessary to evaluate the effectiveness of this approach.

Originality/value

To the best of the authors’ knowledge, this paper is an original attempt to define metaverse tourism in the tourism and hospitality context and to consider its potential, linked to UNWTO’s SDGs. Insights from this paper could be useful for initiating further research and discussions on future metaverse tourism and sustainable tourism.

本研究的目的是定义元宇宙旅游, 并就其在可持续旅游方面的潜力提供关于元宇宙旅游的观点和进一步研究。

本研究基于联合国世界旅游组织 (UNWTO) 报告、谷歌趋势数据以及包括人机交互、虚拟现实和认知研究在内的已有相关研究, 调查了元宇宙在可持续旅游方面的潜力。

这项研究发现, 元宇宙旅游产品和体验可以帮助扩大旅游资源的范围, 并通过提供替代和有利可图的资源来支持可持续旅游。生产许可和盈利的虚拟世界旅游产品和体验可以增加旅游目的地的盈利能力, 并应根据联合国世界旅游组织可持续发展目标 (SDG) 进行开发。

使用元宇宙旅游产品和体验是实现可持续发展目标的一种新方法。未来有必要采取实证研究和案例研究的累积数据进行分析, 以评估这种方法的有效性。

本文是在旅游和酒店环境中定义元宇宙旅游并考虑其潜力的创新性尝试, 与联合国世界旅游组织的可持续发展目标相关联。本文的观点可能有助于启动关于未来虚拟世界旅游和可持续旅游的进一步研究和讨论。

La finalidad de este estudio es definir el turismo de metaverso y proporcionar un enfoque y futuras investigaciones sobre el turismo de metaverso con relación a su potencial para el turismo sostenible.

Diseño/metodología/enfoque

Este estudio analizó el potencial del metaverso para el turismo sostenible basándose en los informes de la Organización Mundial del Turismo (OMT) de las Naciones Unidas, en los datos de Google Trends y en estudios anteriores que incluían las interacciones entre humanos y ordenadores, la realidad virtual y los estudios cognitivos.

Esta investigación encontró que los productos y experiencias del metaverso podrían ayudar a extender la oferta de recursos turísticos y apoyar el turismo sostenible proporcionando recursos alternativos y rentables. La producción de productos y experiencias turísticas de metaverso autorizadas y rentables podría aumentar la rentabilidad de los destinos turísticos y debería desarrollarse de acuerdo con los Objetivos de Desarrollo Sostenible (ODS) de la OMT.

Limitaciones/implicaciones de la investigación

El empleo de productos y experiencias turísticas del metaverso es un nuevo enfoque para alcanzar los ODS. Es necesario analizar los datos acumulados de otros estudios empíricos y de casos de estudio para evaluar la eficacia de este enfoque.

Originalidad/valor

Este documento es un intento original de definir el turismo del metaverso en el contexto del turismo y la hospitalidad y considerar su potencial, vinculado a los ODS de la OMT. Las ideas de este documento podrían ser útiles para iniciar más investigaciones y debates sobre el futuro turismo metaverso y el turismo sostenible.

• Metaverse tourism
• Sustainable tourism
• Virtual reality
• Google trends
• Generation Z and alpha
• 元宇宙旅游、可持续旅游、UNWTO SDGs、虚拟现实、谷歌趋势、Z 世代和阿尔法
• Turismo de metaverso
• Turismo sostenible
• ODS de la IMT
• Realidad virtual
• Generación Z y alpha

Go, H. and Kang, M. (2023), "Metaverse tourism for sustainable tourism development: Tourism Agenda 2030", Tourism Review , Vol. 78 No. 2, pp. 381-394. https://doi.org/10.1108/TR-02-2022-0102

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Copyright © 2022, Emerald Publishing Limited

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Redefining the Future of Travel

Metaverse tourism association.

The go-to organization for virtual tourism professionals. Join us to connect, learn, and grow your career.

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Advocating for a hybrid future of tourism.

At the Metaverse Tourism Association, our mission is to promote the growth and responsible practices of virtual tourism. We advocate for the industry, support inclusion in all forms of travel and provide resources for professionals at all stages of their careers.

“Tourism is a social, cultural and economic phenomenon which entails the movement of people to countries or places outside their usual environment for personal or business/professional purposes. These people are called visitors (which may be either tourists or excursionists; residents or non-residents) and tourism has to do with their activities, some of which involve tourism expenditure.” Definition of Tourism by the UNWTO

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MTA is a community of tourism and metaverse professionals. We believe in the future of travel, a hyrbid future for the tourism industry and adoption of innovative, emerging technologies to harness the true economic power of tourism and hospitality.

Joining the MTA helps your business grow inclusively, introduces you to the brightest minds in the industry, and allows your business or organization to have a bigger impact by collaborating on a collective purpose.

DISCOVER VIRTUAL TOURISM

MTA wants to enable the global tourism community to discover opportunities in the metaverse while promoting an inclusive future of all tourism services and protecting the natural environments of travel destinations. The MTA is creating economic value that benefits both members and tourism bodies globally.

The Metaverse Tourism Association is an organization committed to tourism within the metaverse. Through our members, initiatives and strategic events we wish to explore metaverse potential and drive adoption by fostering new ways for tourism services to build communities within virtual environments.

The MTA also provides a platform for education where individual members and companies are encouraged to share knowledge, collaborate, establish standards and network.

Why Join Us?

• Connect with like-minded professionals.
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The Future of Travel is hybrid! Learn how we can create sustainable tourism models together.

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A new kind of tourism: Virtual travel in the metaverse

You might not need to hop on a plane to travel in the near future. 5g can power a new kind of tourism, one that allows virtual travel to venice, seoul or even the pompeii of the past..

Imagine checking off the destinations on your bucket list—those pricey dream vacations where you stand at the base of the Great Pyramids, the Pompeii of the past, ride a gondola down a canal in Venice or hike the Australian Outback. Or imagine you are touring a luxurious hotel room before paying for it. Instead of committing huge amounts of time or money, you’re researching or experiencing a place that interests you from the comforts of your own home—or from a destination of your choosing.

Thanks to emerging technologies like augmented reality (AR), virtual reality (VR) and edge computing, fully immersive virtual travel is here. And the next frontier in travel may be in the metaverse, where the digital and physical realms merge. In the metaverse, AR and VR can enable people to explore and interact with the destinations and resorts they’ve always dreamed of visiting. With the power of 5G, even the sky is no longer a limit.

Right now, we interact with our devices primarily through sight and sound. As the metaverse develops, the expansion of 5G technology, with its low latency and high throughput, can allow for full multisensory experiences on the go. You may get to hug family members on the other side of the world instead of waving hello through a screen, as many of us did during the pandemic. You might smell fresh baked bread at Parisian cafes or taste a fine wine from the vineyards of Tuscany.

In the metaverse, virtual tourism means a potential significant increase in access to almost any location, personalized guest experiences and enhanced entertainment. For example, museums can offer personalized, immersive tours ; exploring a city could become gamified like Pokemon Go; and restaurants may be able to invite guests to try new dishes from halfway across the world.

“The metaverse when it comes to fruition is going to completely change our lives much like the internet changed our lives,” says Yesha Sivan, visiting professor at the Technion-Israel Institute of Technology and editor-in-chief of the Journal of Virtual Worlds Research .

Multiple metaverses, endless possibilities

According to Sivan, there won’t be one metaverse, but multiple metaverses. In these early days, the metaverse is frequently referred to as a singular entity, but it is likely that there will be many metaverses that will eventually be connected, similar to the way an infinite number of websites exist on the internet. Users will be able to go from one metaverse to another perhaps like catching the Chunnel from London to Paris for a weekend.

Big tech companies, including Disney , Amazon, Microsoft and Meta (formerly Facebook) , are already exploring their own versions of the metaverse. And smaller companies such as Equinox and Delta Reality are interested in working with tourist agencies to develop interactive and even game-like augmented, virtual and mixed reality content highlighting various destinations.

One destination has already taken steps in that direction. In September 2021, Seoul became one of the first major cities to announce plans to go “meta” by 2023. Its metaverse platform, tentatively titled “Metaverse Seoul,” will feature several of the city’s top tourist attractions. Tourists will be able to feel as though they’re walking through Gwanghwamun Plaza, Deoksugung Palace and the Namdaemun Market, in what will be called a Virtual Tourist Zone, without the hassles of in-person travel. They can even “attend” Seoul’s biggest festivals in the metaverse, including the breathtaking Seoul Lantern Festival, surrounded by hundreds of sparkling lights but not by crowds.

Virtual tourism may serve as a springboard to in-person tourism. In early 2022, Madrid launched a free, 360-degree virtual tour in Spanish and English to potential guests who want to make informed decisions about what to see when they visit Madrid in person. With approximately 40 of the capital’s most popular tourist attractions featured, users get a taste of the city, exploring its plazas, museums, gardens, cultural institutions and cathedrals.

“The competitive landscape of the metaverse is getting stronger and stronger,” says Sivan, “and we as consumers love it.”

Making virtual travel easy and seamless

No one likes disruption on vacation, when the idea is to have fun, explore, escape and relax. Users wanting a virtual travel experience will expect the same, meaning that the technology needs to support fluid synchronization between users’ movements and visual perception so that touring a virtual Egypt or Australia will feel as close to real as possible. Reduced latency is critical when creating this level of ultra-sensory content. This is also true for hotels and resorts competing for travelers’ interest, seeking to optimize guests’ stays with personalized packages and seamless experiences. One way to do that in the near future might be offering users three-dimensional AR tours of a hotel, resort or other site.

Think AR and VR , and you immediately envision the headsets users wear to step into these new worlds. The headsets serve as a gateway, Sivan explains, connecting users to a metaverse of their choosing. But the headsets are only one kind of device, and he expects companies investing in their versions of the metaverse to continue to tweak them and other wearables. For example, AR smart glasses and neckbands are already getting significantly lighter with the help of 5G and edge computing. The higher speeds, low latency and additional computing power at base stations and network hubs allow wearables to render graphics remotely in the cloud, making them more power-efficient and enabling a seamless virtual travel experience.

Just the beginning

The travel industry certainly suffered losses and setbacks during the pandemic, but the possibilities of virtual travel may create an entire new sub-sector of tourism. 5G and virtual, augmented or mixed reality metaverse platforms might start a traveler off with trip research before they book an in-person experience.

On the other hand, the technology might eventually lead to fully immersive experiences or to landmarks frozen in history, like the Colosseum at the height of its glory or the ancient city of Pompeii before the catastrophic volcanic eruption. And it seems that this is just the beginning.

“The metaverse first and foremost is a way to conduct our lives,” says Sivan. Companies are “creating a wealth of emerging technologies that are making our lives much more interesting.”

All Verizon customers, new and current, can now get an iPhone 13 on us (128GB)—or up to $800 to put toward a new 5G phone—with select trade-in and select 5G Unlimited plans. 1 Get the details here .

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Katrina Woznicki has traveled to five continents, and her reporting and essays have appeared in National Geographic Traveler, AFAR, The Washington Post, Lonely Planet and U.S. News & World Report , among others. She lives in Los Angeles.

The author has been compensated by Verizon for this article.

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Arizona State University is using technology, including Verizon 5G, to improve the student experience. See what ASU’s president has to say about technology and the future of higher education.

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Navigating the metaverse: unraveling the impact of artificial intelligence—a comprehensive review and gap analysis

• Open access
• Published: 20 August 2024
• Volume 57 , article number  264 , ( 2024 )

Cite this article

You have full access to this open access article

• Mohammed A. Fadhel 1 ,
• Ali M. Duhaim 2 ,
• A. S. Albahri 3 ,
• Z. T. Al-Qaysi 4 ,
• M. A. Aktham 4 ,
• M. A. Chyad 5 ,
• Wael Abd-Alaziz 1 ,
• O. S. Albahri 6 , 11 ,
• A.H. Alamoodi 7 , 8 ,
• Laith Alzubaidi 9 , 10 ,
• Ashish Gupta 10 &
• Yuantong Gu 9 , 10  

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In response to the burgeoning interest in the Metaverse—a virtual reality-driven immersive digital world—this study delves into the pivotal role of AI in shaping its functionalities and elevating user engagement. Focused on recent advancements, prevailing challenges, and potential future developments, our research draws from a comprehensive analysis grounded in meticulous methodology. The study, informed by credible sources including SD, Scopus, IEEE, and WoS, encompasses 846 retrieved studies. Through a rigorous selection process, 54 research papers were identified as relevant, forming the basis for a specific taxonomy of AI in the Metaverse. Our examination spans diverse dimensions of the Metaverse, encompassing augmented reality, virtual reality, mixed reality, Blockchain, Agent Systems, Intelligent NPCs, Societal and Educational Impact, HCI and Systems Design, and Technical Aspects. Emphasizing the necessity of adopting trustworthy AI in the Metaverse, our findings underscore its potential to enhance user experience, safeguard privacy, and promote responsible technology use. This paper not only sheds light on the scholarly interest in the Metaverse but also explores its impact on human behavior, education, societal norms, and community dynamics. Serving as a foundation for future development and responsible implementation of the Metaverse concept, our research identifies and addresses seven open issues, providing indispensable insights for subsequent studies on the integration of AI in the Metaverse.

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1 Introduction

The notion of the Metaverse has recently garnered significant attention and fascination from individuals globally (Cipresso et al. 2018 ; Stephenson 1992 ). The term “metaverse” was introduced by Neal Stephenson in his science fiction novel "Snow Crash" and has since gained popularity through its portrayal in films such as “Ready Player One” (Anon 2023 ). It refers to a virtual reality environment surpassing the physical world’s limitations (Anon 2023 ). The digital world presents an expansive interconnected domain where individuals can engage in diverse activities, interact with others, and fully immerse themselves (Soliman et al. 2024 ). The Metaverse is a dynamic virtual environment that seamlessly incorporates augmented reality, virtual reality, and internet technologies (Wang et al. 2024 ; Carrión, 2024 ). “metaverse” refers to a complex network of interconnected virtual spaces, worlds, and experiences rather than a singular platform or application. Consider a hypothetical scenario where individuals have the ability to transport themselves to vibrant urban centres instantaneously, traverse imaginative terrains, participate in simulated musical performances, partake in immersive gaming encounters, or construct and manipulate personalized digital domains (Wang et al. 2022 ). Within the Metaverse, individuals have the ability to embody digital avatars, which are personalized depictions of themselves, thereby facilitating engagement with the virtual environment and other users. The avatars can be customized to reflect the users’ distinct characteristics, inclinations, and ambitions. The Metaverse strives to achieve a heightened sense of presence by leveraging sophisticated technological capabilities such as haptic feedback, motion tracking, and realistic graphics, thereby blurring the boundary between the physical and digital worlds. A central focus on collaboration and social interaction characterizes the metaverse experience. Individuals hailing from diverse geographical locations have the ability to converge, interact, and exchange personal encounters instantaneously. The Metaverse facilitates a global sense of community and connectivity through virtual meetings, collaborative projects, or socializing with friends (Bansal, 2024 ).

The phenomenon extends beyond geographical boundaries, allowing individuals to establish significant connections and cultivate relationships regardless of their physical location (Anon 2023 ). The Metaverse offers a plethora of opportunities for commerce, entertainment, and education without any apparent limits. Enterprises have the capacity to create virtual storefronts and offer immersive shopping experiences. In contrast, artists and creators have the opportunity to exhibit their work and interact with their audience in novel and stimulating manners (Anon 2023 ). Virtual events, concerts, and conferences have the potential to reach a worldwide audience without the limitations of physical locations. Academic institutions have the potential to utilize the Metaverse as a tool for developing interactive learning environments, which can facilitate students’ exploration of various subjects through immersive and captivating means. Furthermore, scholarly inquiry has extensively investigated the incorporation of AI and blockchain technologies into the Metaverse, in addition to virtual reality (Mu et al. 2024 ). These studies explore the implementation of AI applications within virtual environments and the potential for blockchain-based technologies to improve the capabilities of the Metaverse. Through an analysis of the convergence of these technologies, scholars endeavour to furnish a holistic comprehension of their contributions to the formation of the Metaverse and the realization of its potential utilities.

Additionally, the scholarly inquiry has been undertaken to comprehend the technical intricacies and system architecture necessary for the efficacious establishment and functioning of the Metaverse (Suo et al. 2024 ). The aforementioned studies tackle crucial concerns about the precision of motion capture, the stability of systems, and the safeguarding of data and privacy in virtual environments. Through comprehensive exploration of these facets, scholars endeavour to develop resilient and effective systems that can facilitate the multifarious functionalities of the Metaverse. Besides technical aspects, scholarly investigations have also delved into the ethical and cultural ramifications of the Metaverse (Cao et al. 2024 ). Scholars have conducted thorough investigations into the intersection of simulation and reality, elucidating the workings of novel profit models and their effects on cultural production. Through the analysis of practical applications and conceptual models, scholars endeavour to attain a more profound comprehension of the ethical facets of the Metaverse and its wider societal ramifications (Gokasar et al. 2023 ; Mohammed et al. 2023 ). The Metaverse harbours prospects surpassing entertainment and technology, as evidenced by its potential to offer substantial opportunities in the healthcare sector (Mozumder et al. 2022 ). Research has been conducted to examine the amalgamation of the IoT, AI, and other technological advancements within the Metaverse to enhance healthcare services (Saihood et al. 2024 ; Alammar et al. 2024 ). By utilizing the functionalities of this digital world, scholars aim to augment patient-focused healthcare, medical pedagogy, cooperation, and inclusivity in the healthcare sector. Additionally, scholars have conducted investigations into the social and cultural aspects of the Metaverse, examining its influence on the development of identity and interpersonal relationships (Cheng et al. 2022 ). The present research endeavours to scrutinize the ways in which individuals maneuver and project their personas in digital worlds while assessing the potential consequences for their self-concept and interpersonal connections. Researchers aim to gain insight into the transformative capacity of the Metaverse, in terms of shaping human behaviour and societal norms, by comprehending the dynamics of social interactions within this virtual world. Moreover, the economic facets of the Metaverse have garnered considerable interest. Research has been conducted to explore the possibility of novel business models and sources of income in this digital world (Jafar et al. 2024 ). Scholars examine the potentialities of virtual commerce, digital assets, and virtual currencies alongside the difficulties linked to commercializing and safeguarding intellectual property rights.

The objective of these investigations is to offer perspectives on the economic mechanisms of the Metaverse and their probable consequences for sectors such as gaming, entertainment, and e-commerce. Furthermore, the education sector has been investigating the incorporation of the Metaverse into educational settings. Scholars have investigated using virtual reality and immersive encounters to augment educational methodologies (Rogdakis et al. 2024 ). The authors investigate the potential of the Metaverse in facilitating interactive and immersive learning environments that promote collaboration, creativity, and knowledge acquisition. The objective of these investigations is to reveal the capacity of the Metaverse to revolutionize conventional pedagogical methods and equip students with the necessary skills for the contemporary digital era. Additionally, scholars have explored the potential of the Metaverse in tackling societal issues and advancing inclusiveness. The authors investigate the potential of virtual environments in mitigating geographical and social disparities, as outlined in (Chuang et al. 2021). The Metaverse has the capacity to facilitate cultural exchange, collaboration, and understanding among individuals from various backgrounds by offering accessible and immersive experiences. The objective of these investigations is to examine the societal ramifications of the Metaverse and its capacity to foster a more comprehensive and interconnected community. Recently, in the discourse of the metaverse concept, Apple’s Vision Pro presentation employed a distinctive methodology in contrast to other corporations such as Meta. Apple’s approach was centred on leveraging their pre-existing applications to augment the user’s experience rather than prioritizing virtual environments and total immersion. The Vision Pro headset was introduced to enhance routine tasks and endeavours.

During its presentation, Apple demonstrated the potential of mixed reality technology to enhance FaceTime functionality Anon (2022a). This innovation lets users simultaneously engage in a video chat while accessing other pertinent windows. The authors additionally exhibited the utilization of Safari in a virtual environment, wherein numerous sizable windows were exhibited, thereby obviating the necessity for multiple monitors. The availability of several widely used applications such as photo browsing, Disney + streaming, Microsoft Office, and Adobe Lightroom on VisionOS has been confirmed by Apple. Apple’s strategy distinguishes its mixed reality headsets from others by making users perceive that the device would yield tangible advantages in their everyday routines. Despite persistent concerns regarding the elevated cost and restricted battery longevity, Apple has prioritized marketing the Vision Pro headset and the comprehensive notion and potential of spatial computing. In contradistinction to the nomenclature "metaverse" employed by other corporations, Apple has introduced the phrase "spatial computing" as their chosen terminology. The notion appears to be more tangible and comprehensible, given its emphasis on incorporating digital material into the physical world, as opposed to developing a wholly virtual environment. The notion of spatial computing has been posited as a more compelling prospect for the future of computing when juxtaposed with the previously promoted concept of the Metaverse. The marketing strategy employed by Apple exhibited a comprehension of user requirements and a dedication to the smooth incorporation of technology into daily routines (Anon 2023 ). To conclude, the notion of the Metaverse has generated significant interest and scholarly inquiry across diverse fields. The investigation of virtual reality technology, artificial intelligence, blockchain, healthcare, societal implications, and other related areas has brought to the fore the extensive possibilities and difficulties linked with this digital world Anon (2022b). Scholars strive to comprehend the ramifications of this phenomenon on various aspects of human conduct, financial systems, academic institutions, societal norms, and the broader community. The results of these investigations provide a foundation for the future advancement, application, and conscientious execution of the Metaverse.

The correlation between AI advancements and the emergence of the Metaverse is unmistakable, but it’s crucial to recognize AI’s causative role in shaping and enabling its development. The interaction between AI and the Metaverse is an important topic of research, particularly since AI has a significant impact on the Metaverse’s development and functioning. When looking at the impact of AI on Metaverse realisation, it is crucial to discern between correlation and causality. While it is widely acknowledged that AI technologies are intrinsically tied to the development of the Metaverse and play an important role in enabling many of its features and capabilities, it is necessary to recognise that correlation does not necessarily imply causation. In other words, just because AI and the Metaverse are inextricably linked does not mean that AI is the fundamental cause of their formation or development. Instead, further study is required into the specific ways in which AI contributes to the Metaverse’s realisation, such as an analysis of the causal links between AI technologies and various aspects of the Metaverse’s design, operation, and user experience. This might entail investigating how AI-powered algorithms manage virtual environments, streamline user interactions, tailor experiences, generate content, and increase immersion in the Metaverse (Soliman et al. 2024; Fadhel et al. 2024a , b , c ).

The developing Metaverse is inextricably tied to advances in AI, a connection destined to transform digital interaction. At its heart, AI enables the seamless integration of virtual surroundings with human encounters. Users may easily interact with virtual creatures, navigate immersive environments, and collaborate with others using spoken or written language thanks to powerful NLP and conversational AI. Furthermore, AI-powered virtual characters and NPCs improve realism by reacting dynamically to user activities and participating in realistic discussions. This integration of AI and the Metaverse goes even further, as machine learning algorithms analyse user behaviour to personalise experiences, produce varied virtual worlds using procedural generation methods, and govern virtual economies using predictive analytics. In the world of immersive experiences, AI enhances VR surroundings with realistic physics, animations, and visuals, creating a stronger sensation of presence. Furthermore, AI-powered social algorithms foster communities in the Metaverse by suggesting content and enabling meaningful interactions (Zhuk 2024 ). The contributions of AI in the Metaverse can be summarized as follows:

Incorporating AI into the Metaverse facilitates a heightened level of immersion by generating captivating and lifelike virtual environments. Integrating AI-based elements, such as dynamic environments, intelligent NPCs, and interactive objects, significantly enhances the overall user experience and interaction quality.

AI holds a pivotal position in the Metaverse, enabling the progression of complex NPCs with lifelike behaviours and decision-making capabilities. As a result, this phenomenon gives rise to the development of virtual environments that exhibit increased interactivity and captivation, consequently augmenting the overall user experience.

The AI algorithms employed in the Metaverse are designed to examine user preferences and behaviours to produce personalized content customized to individual interests. This process ultimately enhances the relevance and enjoyment of virtual experiences for users.

Utilizing AI-powered chatbots and virtual assistants within the Metaverse is essential as they facilitate seamless and genuine social interactions among users. This, in turn, fosters a sense of community and elevates user engagement levels.

AI is critical in optimizing resource allocation and utilization within the Metaverse, ensuring the efficient distribution of computational power, storage, and network resources, and enhancing overall performance and scalability.

The AI algorithms utilized by the Metaverse proficiently analyze large volumes of data in real-time, enabling the capability to adjust to virtual environments based on user interactions, feedback, and changes in the environment.

The incorporation of AI technologies within the Metaverse significantly impacts the preservation of safety protocols and the observance of ethical standards. AI-driven content moderation, detection and prevention of harmful activities, and safeguarding users’ privacy and personal information are essential roles fulfilled by social media platforms.

This paper makes a significant contribution by conducting a thorough analysis of studies to create a comprehensive taxonomy of AI in the Metaverse. Emphasizing the importance of trustworthy AI, the paper underscores its role in enhancing user experiences, safeguarding privacy, and promoting responsible technology use within the Metaverse. Also, we aim to dissect the causal mechanisms underlying AI’s influence on the Metaverse, shedding light on its profound impact and ethical considerations. Furthermore, it highlights the substantial scholarly interest and research on the Metaverse, examining its implications for human behaviour, education, societal norms, and community. The findings not only serve as a foundation for further development and implementation of the Metaverse concept but also identify and address seven critical open research issues, providing valuable insights to guide future studies on the integration of AI in the Metaverse.

The organization of this paper is structured in the following manner. The technique of doing a systematic literature review is outlined in Sect.  2 . Section  3 encompasses three comprehensive scientific mapping studies that use a bibliometric approach to identify trends and deficiencies within the existing literature, therefore enhancing the understanding of the subject matter. Section  4 delineates the study’s findings, with particular emphasis on seven significant domains. Section  5 delves into the enrichment of incentives, challenges, and recommendations pertaining to AI inside the Metaverse. Section  6 of the paper undertakes an evaluation of five distinct traits and identifies research gaps within the domain of AI in the Metaverse. This analysis serves as a foundation for proposing potential areas of investigation and advancement in the future. Lastly, the concluding section, Sect. 7 , brings this contribution to a conclusion.

2 Methodology

The methodology used in this work followed the recommended reporting guidelines for a systematic review and meta-analysis, as seen in Fig.  1 (Khaw et al. 2022 ; Sohrabi et al. 2021 ). The research approach included using many bibliographic citation databases, including various medical, scientific, and social science articles across various disciplines. The researchers used four prominent digital databases, namely SD, Scopus, IEEE, and WoS, to conduct a comprehensive search for the desired articles. These databases provide valuable insights to scholars by offering comprehensive coverage of research across several scientific and technology fields.

Depicts an overview of the technique used to discover, select, and incorporate essential contributions

2.1 Search methodology

A comprehensive search was conducted across four databases, namely SD, Scopus, IEEE, and WoS, in order to identify academic papers written in English. This search included all articles published from the beginning of scientific output until April 2023. The search conducted in this study used a boolean query consisting of a single operator (AND) to connect the terms "metaverse" and " Artificial Intelligence " (refer to Fig.  1 ). These keywords were selected by the collaboration of domain specialists specializing in AI and Metaverse. There are further prospects for using metaverse components inside artificial intelligence, including augmented and virtual reality.

2.2 The concept of inclusion and exclusion criteria

Within systematic literature reviews, the inclusion and exclusion criteria have a crucial function by offering explicit guidance for the selection of research based on specified criteria. These criteria are crucial for ensuring that the studies included in the review are in line with the study aims and scope, thereby improving the rigour and relevance of the results. The current research took into account the following criteria:

The article was authored in English and published in either an academic journal or a conference paper.

The chosen research must have a strong correlation with both the metaverse and the components of Artificial Intelligence.

The article should enhance data fusion in the metaverse by using Artificial Intelligence and ML/DL, guaranteeing information of superior quality and free from errors.

On the other hand, the article’s concentration and significance were maintained by using exclusion criteria to exclude research that did not fit within the specified scope.

Articles are written in a non-English language.

This article specifically examines the metaverse and Artificial Intelligence, excluding studies that merely briefly touch upon these topics.

Any review or empirical research that do not include a significant recommendation related to a particular hypothesis are rejected.

2.3 Study selection

Similar to previous studies (Khaw et al. 2022 ; Sohrabi et al. 2021 ) this study used the PRISMA guidelines to conduct a comprehensive literature review. This technique consists of many steps, with the first stage removing duplicate documents. The Mendeley tool was used to conduct a comprehensive scan of the titles and abstracts of the submitted materials. This methodology included the whole of the writers and entailed the removal of several irrelevant literary works. The author addressed and resolved inconsistencies and conflicts within their work. The subsequent phase included thoroughly reviewing the whole text and eliminating content not aligning with the predetermined inclusion criteria. Three experts evaluated the filtering technique’s effectiveness (refer to Fig.  1 ).

The papers that satisfied the specified criteria were included in this research. The search yielded 846 papers, with the majority (523) sourced from SD. Scopus contributed 162 articles, while IEEE and WoS accounted for 86 and 75, respectively. The search included all publications from the inception of scientific output until April 2023. After removing around 45 duplicate entries from the four databases, the overall count of articles was reduced to 801. Upon careful examination of the titles and abstracts, 706 articles were excluded from consideration. A thorough and rigorous assessment of the remaining 95 submissions found that 41 articles needed to meet the eligibility requirements. Consequently, only 54 research papers were judged relevant and subsequently included in the final selection of publications based on the predefined inclusion criteria. The subsequent part delineates using several bibliometric methodologies to monitor the analysis of acquired articles.

3 Comprehensive science mapping analysis

Numerous researchers have proposed methodologies to enhance the comprehensiveness of scientific mapping analysis by using R-tool and VOSviewer (Wu and Zhang 2024 ; Fadhel et al. 2024). These approaches aim to improve the transparency of presenting the findings from the 54 investigations. The bibliometric technique is characterized by its excellent reliability and transparency, enabling the production of dependable results, identification of research gaps, and derivation of conclusions from the existing literature. Therefore, the bibliometric technique outlined in the subsequent subsections was used in this investigation.

3.1 Annual scientific production

Over the previous decade, the Metaverse has grown significantly, including AI advancements. Figure  2 depicts the annual scientific output, demonstrating the evolution of prior theoretical and practical investigations on the Metaverse. Figure  2 displays the yearly academic output concerning AI’s influence on the Metaverse. The amount of publications has increased significantly in recent years, as seen by the small number of papers published in 2011 and 2013. The number of articles increased steadily during 2021, reaching a high of 39 articles in the following year, 2022. The aforementioned trend held true for 2021 and 2022, with 3 and 39 papers published, respectively. As of now, in the early stages of the year of 2023, the number of articles published stands at a modest nine. The available statistics show a steady and ongoing growth in scholarly papers about the Metaverse.

Annual scientific production

During the years 2021 and 2022, the Metaverse witnessed a significant resurgence, which was propelled by technological progress and industry momentum, resulting in a surge in scholarly investigations. Nevertheless, progress reached a halt in 2023 as a result of technological impediments, regulatory ambiguity, and alterations in economic objectives. Notwithstanding these obstacles, academics persisted in participating in critical dialogue and cooperating to tackle ethical concerns in an attempt to actualize the Metaverse’s capacity for profound change.

3.2 Word cloud

Word cloud analysis has enabled the identification of the most prevalent and significant keywords within prior scholarly research. Figure  3 presents a comprehensive depiction of the essential concepts that have been derived from prior research findings. Its purpose is to summarize and reorganize the existing body of knowledge succinctly.

The relatively small size of keywords implies a reduced likelihood of their occurrence. Based on the term frequencies depicted in Fig.  3 , it is apparent that numerous significant topics pertaining to the ‘metaverse’ domain are frequently the subject of discussion. The subjects that demonstrate the highest frequencies are ‘artificial intelligence’, ‘deep learning’, ‘virtual reality’, ‘machine learning’, ‘blockchain’, and ‘augmented reality’. Moreover, the data presented demonstrate the substantial relevance of the topics of 'deep learning' and 'virtual reality' within the given domain. Other relevant terms that are closely linked to the subject matter encompass “image classification”, “immersive experience”, “virtual worlds”, “CNN”, “gesture recognition”, and “human–machine interfaces”. The notable prevalence of these terms highlights the importance of considering these factors when designing and deploying AI systems. Figure  3 showcases various applications of AI in diverse domains, such as ‘Avatar’, ‘3D human reconstruction’, ‘3D model’, ‘3D point cloud’, and ‘3D virtual world’. Additionally, the text emphasizes different methodologies utilized within the domain of AI, such as CNNs, natural language processing, and robotics. The examination of the word cloud generated from Metaverse based on AI papers reveals a wide-ranging scope within the discipline, encompassing various subjects such as the technical aspects of AI and strategies for its implementation.

3.3 Co-occurrence

A co-occurrence network is an additional tool utilized in bibliometric analysis. Previous scholarly investigations have undertaken the task of identifying and examining commonly utilized terms and conducting their analysis. The aforementioned studies have primarily concentrated on examining a semantic network, which has proven to be a valuable resource for professionals, policymakers, and scholars in understanding the conceptual framework within a particular knowledge domain. The data presented in Fig.  4 pertains to a co-occurrence network that has been constructed utilizing the titles of scholarly articles focused on Metaverse based on AI.

Co-occurrence network

The network comprises nodes, which symbolize the individual words in the titles. The edges that establish connections between the nodes represent the frequency with which these words co-occur within the same title. The diagram in Fig.  4 depicts several nodes and their corresponding clusters and closeness centrality values. These values measure the degree of interconnectedness between a node and other nodes in the network. The nodes demonstrate a noticeable arrangement, displaying 14 separate clusters. Every cluster exhibits a set of words with a thematic or conceptual association with Metaverse AI. Cluster 1 comprises Metaverse, artificial intelligence, blockchain, immersive experience, virtual worlds, 2D to 3D converter, 3D point cloud, 3D virtual world, avatar, and content delivery networks. The aforementioned terms signify that the cluster is associated with applying metaverse AI systems in medicine. Cluster 2 comprises terms such as ‘deep learning’, ‘virtual reality’, ‘machine learning’, ‘3D model’, ‘anomaly detection’, ‘big data’, and ‘body motion recognition’, suggesting that this cluster is associated with the various aspects of artificial intelligence. Similarly, additional clusters demonstrate connections with topics such as augmented reality, reading in AR, and asymmetric virtual environments. Determining a node’s centrality in a network is based on its closeness, which can be understood as a metric of its importance. Words that have higher closeness values demonstrate stronger connections to other nodes in the network, indicating their greater centrality about the topic of metaverse AI. The diagram succinctly depicts the interconnectedness between concepts and terminologies related to metaverse AI, as evidenced by the titles of scholarly articles in this field. The information provided has the potential to help understand the current state of research in this field and identify areas that require further investigation.

4 Results and analysis: a taxonomy

Metaverse was built using the conducted technique, and the final collection of articles met the considered inclusion and exclusion criteria. Furthermore, based on objective evidence from studies that met these criteria, the 54 publications were divided into seven basic categories (see Fig.  5 ). These categories are related to:

Metaverse in VR: including 17 of 54 papers.

Metaverse Integration with AI and Blockchain: including 4 of 54 papers.

Agent-Based Systems and Intelligent NPCs in the Metaverse: including 3 of 54 papers.

Metaverse’s Societal and Educational Impact: including 6 of 54 papers.

HCI and VR Applications in the Metaverse: including 16 of 54 papers.

Systems Design and Technical Aspects of the Metaverse: including 4 of 54 papers.

Metaverse Reviews: including 4 of 54 papers.

AI Integration in metaverse taxonomy

4.1 Metaverse in VR

Virtual Reality and the Metaverse are transforming the digital landscape by combining physical and digital worlds. Virtual reality immerses users in realistic simulated environments, while the Metaverse offers a shared virtual space for real-time interaction and transcends traditional limitations. These technologies promise to revolutionize industries and redefine digital experiences, with Virtual Reality as a fundamental component of the Metaverse. The literature explores this connection in 17 out of 64 articles discussing the potential of virtual reality within the Metaverse universe. Researchers have proposed various algorithms and models to enhance virtual environments and human reconstructions. (Su et al. 2022 ) presents a 3D human reconstruction algorithm, combining facial features and 2D image features to predict 3D human body parameters. The proposes a learning model in (Arroyo, Serradilla, and Calvo 2011) merging evolutionary computation and fuzzy controllers to optimize the movement of metabots, enhancing their autonomy and interaction in virtual worlds. (Fan, Chiu, and Chang 2022) introduces an algorithm for automatic depth information map generation using overlapping lines. Furthermore, (Park et al. 2022 ) proposes a grouping algorithm to secure topics for security and safety within the Metaverse, improving topic-based models’ accuracy. Researchers address privacy and identity concerns in the Metaverse by developing a superior finger vein recognition system using deep learning and anti-aliasing techniques (Tran et al. 2023 ). They also create an AI-based system to teach ArSL using avatars in AR and VR, benefitting people with hearing loss (Batnasan et al. 2022 ). Another study focuses on using AR to distinguish emotional states during book reading activities using EEG signals, demonstrating high classification performance (Dasdemir 2022 ).

The potential data-related issues and power inequities in VR technology are examined using Facebook’s Oculus VR as a case example. Three studies (Egliston and Carter 2021 ; Jian et al. 2022; Sun et al. 2023 ) discuss the impact of VR on society and human existence. They highlight concerns such as exacerbating wealth inequality, algorithmic bias, and digital exclusion, calling for regulatory intervention. Additionally, they explore the potential risks of addictive dependence and escapism while acknowledging the transformative possibilities of the "Metaverse." One study (Cho et al. 2022 ) focuses on designing a DAVE to optimize VR and AR experiences. Another aspect explored is the concept of hyperproduction, examining the implications of AI-generated media on cultural production. The study explores the convergence of simulation and reality in the context of rentier capitalism (Ferrari and McKelvey 2022). It presents four propositions for Metaverse tourism, emphasizing immersive experiences and multi-identification profiles (Koo et al. 2022 ). The research examines IoT, Blockchain, and AI use in medical healthcare within the Metaverse (Mozumder et al. 2022). Additionally, it discusses AI’s role in advancing Metaverse technologies (Cheng et al. 2022 ). The integration of Metaverse with extended reality technologies for healthcare improvement is also explored (Ahuja et al. 2023 ). Another paper focuses on speech interactions for aircraft maintenance in the Metaverse (Siyaev and Jo 2021).

4.2 Metaverse integration with AI and blockchain

Integrating AI, blockchain, and the Metaverse drives progress in the digital world. AI enhances immersive experiences with personalized content, while blockchain ensures transparency and ownership of digital assets. This synergy creates a dynamic ecosystem, fuelling gaming, finance, and commerce opportunities. Ultimately, this powerful amalgamation reshapes how people interact, transact, and navigate the digital world, forming a blockchain-based decentralized network of virtual worlds and 3D settings. Metaverse is a simple platform for anyone to develop their virtual world or 3D environment. In this context, this category includes 4 of 54 articles.

Authors in (Choi and Kim 2022 ) analyzed satisfaction with virtual object manipulation in the Metaverse based on MR, conducting experiments and assessing two properties: manipulation and virtual object. A study (Bouachir et al. 2022 ) explores AI’s potential in decision-making simplification, task automation, and Blockchain optimization in the Metaverse. It reviews Blockchain technology’s role and the impact of AI on intelligent Blockchain features, promising improved Metaverse ecosystem integration. In paper (Gupta et al. 2022 ) investigates AI’s role in the Metaverse’s establishment, exploring AI-based methods and potential applications and providing insights for researchers. Lastly, the study (Zhou 2022 ) reflects on a journal’s accomplishments, showcasing collaborative efforts between IEEE and the Chinese Association of Automation, serving as a model for future collaborations. It also talks about the possibilities of Metaverse and how it can be used in different fields.

4.3 Agent-based systems and intelligent NPCs in the metaverse

Agent-Based Systems and Intelligent NPCs play a crucial role in the Metaverse, enhancing immersive experiences. These systems use advanced AI algorithms to create lifelike virtual characters capable of interactive behaviour. NPCs in the Metaverse exhibit human-like behaviour, dynamically adapting and acquiring knowledge based on user interactions, resulting in engaging experiences. The integration of these technologies redefines virtual storytelling and interpersonal interactions, elevating the overall authenticity and engagement within the virtual environment. This category explains that virtual agents inhabiting the Metaverse will be self-contained, three-dimensional objects comparable to the non-realistic chatbots and speech bots currently in use and includes 3 of 54 papers.

The authors used DRL technology and the Metaverse to optimize emergency evacuations, offering a training system for evacuees to find the quickest route to exit buildings. They utilized sensor data for real-time building status monitoring (Gu et al. 2023 ). A multi-agent reinforcement learning framework was proposed to enhance intelligent non-player characters in the Metaverse, allowing personalized learning (Hare and Tang 2022 ). Additionally, a method was suggested to improve motion capture for CG avatars during interactions by supplementing a user’s motion with another person’s motion, resulting in more natural avatar movements (Suzuki, Mori, and Toyama 2022 ).

4.4 Metaverse’s societal and educational impact

The Metaverse is transforming society and education. This virtual environment changes how people interact, collaborate, and do business in a digitally connected world. Metaverse immersive learning experiences promote active engagement and knowledge retention in education. However, the effects of AI on privacy, digital identity, and social dynamics require careful regulation to maximize its potential for social and educational progress. Early technology applications show that metaverse education can be democratized. This category includes 6 of 54 articles.

The editorial will explain why interactive learning environment users may want to enter the Metaverse cautiously. To adequately outline these risks, the Metaverse must be defined, its technologies used, and how it can be used for learning and teaching (Rospigliosi 2022 ). They presented XIVA, an intelligent voice assistant for Chinese voice interaction in future educational metaverse systems. The open programming interfaces that allow third-party developers to create new voice commands and functions set XIVA apart. XIVA’s essential voice interaction and third-party extensions for smart classroom operation control are shown in the study (Lin et al. 2022 ). This study introduced a gesture recognition system using triboelectric smart wristbands and an AAL model. The wristbands’ anatomical design allows for highly sensitive and high-quality sensing, enabling accurate gesture recognition with low computational costs. The study shows that real-time somatosensory teleoperations can transform cyber-human interactions and provide immersive experiences (Fang et al. 2022 ).

Metaverse construction image classification can be improved with a CWCT transformer. CNN and transformers use an optimized Cross-Window Self-Attention mechanism to capture local and global features of high-resolution images, improving classification accuracy and model complexity (M. Li, Song, and Wang 2022 ). To examine how the metaverse age affects college students’ network behaviour and university ideological and political education. The study examines intelligent technology’s background, college students’ network behaviour, its multifaceted effects, and its nature to improve ideological and political education (Ge 2022 ). Implement a virtual world using GNU OpenSimulator and investigate metaverses in education. The researchers develop a metaverse-based expert systems course methodology that measures server performance and predicts server behaviour using time series analysis (Gonzalez Crespo et al. 2013 ).

4.5 HCI and VR applications in the metaverse

HCI and VR are merging to change how people use technology. HCI is the academic study of user interface design and implementation to improve human–computer interaction. VR technology simulates virtual environments to give users immersive experiences. HCI and VR convergence improves user experiences by enabling more genuine and immersive interactions. These technologies’ convergence could benefit gaming, education, and healthcare. HCI and VR advancements drive innovation and transform our engagements with digital content, improving our daily lives. The success of the Metaverse depends on HCI, mainly on how to feed user actions into the virtual environment. This category includes 16 of 54 articles.

A new study proposed an SDN IoT intrusion detection model under a 5G mobile network that combines traditional machine learning with deep learning to process traffic in linear sequence using DAE, GAN, and random forest for the future metaverse security problem. The DAE algorithm extracts and displays data features, the GAN algorithm optimizes and balances data, and the random forest algorithm classifies (Ding, Kou, and Wu 2022). Another research describes a skin-interactive electronic sticker in a hybrid cartridge (disposable bandages and non-disposable kits) that digitally decodes epidermal deformation. The gadget may be used in two ways: as a tiny electronic sticker with a thickness of 76 m and a node pitch of 7.45 mm for static body curvature measurement and as a wrist bandage for dynamic skin wave decoding into a colorful core-line map. This approach has a feedforward deep learning F1 score of 0.966 due to its high detection sensitivity in static mode and high accuracy of 0.986 in dynamic mode. By analyzing skin thicknesses and locations through picture segmentation, the gadget can decode 32 delicate finger folding actions, resulting in an optimum color map core line.

This method may help researchers better comprehend skin wave deflection and variations for wearable applications such as sensitive skin-related gesture control in the Metaverse, brain-degenerate rehabilitation programs, and digital medicine biophysical status detectors for body form and curvature (Hong, Lee, and Lee 2022 ). This research aims to create the AIOM touch sensor, a two-electrode multipoint touch sensor that can adapt to diverse setups effectively. This touch sensor can recognize, learn, and remember human–machine interactions, allowing for biometric authentication and interactive virtual object control (Wei et al. 2022 ). This study uses TTS and deep learning to create an intelligent non-contact gesture recognition system. The system accurately recognizes diverse, complex gestures without accessories or complex sensing platforms, making it suitable for touchless medical equipment, public facilities, smart robots, virtual reality, and metaverse (Zhou et al. 2022 ). This paper examines modern book layout design in colleges and universities in the educational Metaverse. The study emphasizes artistic value and creative language design strategies in book layout and proposes a layout analysis and text image preparation algorithm for university book layout design (Sun 2022 ). A simple, intelligent meta-learning system is being developed for the strengthened Metaverse during the COVID-19 pandemic. The study designs and creates a virtual learning environment using Open Simulator and Moodle to support students with different abilities, track their activities, and evaluate their performance, particularly in mathematics (Sghaier, Elfakki, and Alotaibi 2022). To investigate the possible uses of the Metaverse in healthcare and propose a metaverse of MeTAI to aid in the development, evaluation, and regulation of AI-based medical practices, notably in medical imaging. The research looks at use cases, challenges, and action items for developing the MeTAI metaverse to enhance healthcare quality, accessibility, cost-effectiveness, and patient happiness (Wang et al. 2022 ). The work presents a data-driven power coordination management strategy to increase PEMFC stability, performance, and efficiency.

To coordinate agents with distinct aims, the paper offers a metaverse-based multiagent double delay deep deterministic policy gradient (MET-MADDPG) method (J. Li, Yang, and Yu 2022 ): a DNN-based 3D-to-2D watermarking approach for Metaverse immersive material copyright protection. The research intends to assist authors of immersive material in protecting their copyrights and ownership (Park et al. 2023 ). To illustrate how the inherent anisotropy of tellurium nanowires influences electrical structure and piezoelectric polarization, allowing VR interaction and neuro-reflex. The researchers created a wearable glove with a bimodal Te-based sensor for improved somatosensory feedback in virtual reality, as well as successful stimulus recognition and neural reflex in a rabbit sciatic nerve model, demonstrating potential applications in the Metaverse, AI robotics, and electronic medicine (L. Li et al. 2022a , b , c ). To overcome electrode shifts in VR headsets that damage facial EMG based FER systems. The work suggests adopting covariate shift adaption approaches in the feature and classifier domains to increase system resilience and maintain high classification accuracy even when electrodes are removed and reattached, making fEMG-based FER more suitable for VR-based metaverse applications (Cha and Im 2022 ). This research aims to increase the training stability and speed of GANs in the Metaverse for human picture synthesis and modification. The study proposes novel methods for improving rendering and spectral normalization and using Residual Fast Fourier Transform Block and Wasserstein distance to improve GAN training stability and efficiency, demonstrating their effectiveness through experimental evaluations and achieving state-of-the-art image quality metrics (Wu et al. 2022 ).

This study aims to create a soft electronic glove compatible with skin and thermal transfer-printed. This glove will allow for seamless and natural interactions between people and XR equipment in the Metaverse. The glove identifies hand motions and operates VR applications in a customized shooting game utilizing low-cost, lightweight, and mass-producible materials (Xia et al. 2022 ). This research tackles the difficulties in identifying singers in the Metaverse induced by live effects. To enhance singer identification, the research employs MMD, gradient reversal (Revgrad), and CAN with CRNN. On the Artist20 dataset, CRNN-CAN produced cutting-edge F1 findings (X. Zhang et al. 2022a , b ). Additionally, VR, Metaverse, and AI technologies were employed to improve football education on mobile internet platforms. The paper presents a K-means-based optimal distribution approach for 360-degree panoramic VR football teaching videos. It assesses its efficiency using simulation experiments in order to enhance teaching and promote football teaching and smart learning (Li, Cui, and Jiang 2022). A hybrid system that combines AI-generated material with user-generated content generates interactive fiction and allows users to participate in narrative exchanges with the AI agent (Sun et al. 2022 ).

4.6 Systems design and technical aspects of the metaverse

Systems design and technology shape the Metaverse’s development and operation. The virtual domain needs resilient systems for network infrastructure, data storage, and security to handle its size and complexity. AI, blockchain, and cloud computing help create immersive experiences and instantaneous Metaverse interactions. To create a cohesive and sustainable ecosystem, scalability, interoperability, and standards must be analyzed. The Metaverse’s design and technical implementation affect its usability, stability, and growth. 3D design technologies can improve metaverse design and development, giving consumers more engaging and immersive experiences. This category includes 4 of 54 articles.

The VADER sentiment classifier improves online review sentiment analysis for mobile metaverse applications. The study compares machine learning classifiers using different embedding methods and finds that VADER-based classifiers outperform those that do not, with LightGBM and TF-IDF having the highest accuracy (Lee et al. 2022 ). This paper uses virtual and real methods to address transportation structure design, vision models, data security, and privacy in virtual transportation space. The paper examines how virtual transportation can manage these aspects to ensure functionality and safety (Zhang et al. 2022a , b ). This metaverse-based InfoMat study will create a digital-twin smart home. The InfoMat is used for smart home monitoring, position sensing, user identification, and virtual reality visualization to overcome unstable TENG output under environmental changes (Yang et al. 2023 ). Identify virtual 3D asset pricing factors and create a machine-learning model to predict them. The study highlights creators’ subjective assessments of virtual 3D assets as a significant factor in pricing behaviour (Korbel et al. 2022 ).

4.7 Metaverse reviews

Reviewing a topic emphasizes critical thinking. This study analyzes the topic’s pros, cons, and significance. Reviews help consumers, researchers, and audiences make informed decisions. Through feedback and constructive criticism, reviews help creators and providers improve products, services, and content. This category provides insight into previous works in the literature for a Metaverse review and includes 4 of 54 articles.

This study covers state-of-the-art head motion monitoring systems based on inertial sensors, including acquisition methods, prototype structures, pre-processing steps, computational methods, and validation methods. The study utilizes machine learning algorithms to monitor head motion and contextualizes inertial sensor technology for paralysis (Ionut-Cristian and Dan-Marius 2021 ). The study examines how AI has helped create and advance the Metaverse, a shared virtual world powered by emerging technologies. The study covers AI, including machine learning and deep learning, and explores AI-based methods in six metaverse-relevant technical areas and potential AI-aided applications in various fields. The survey concludes with critical contributions and metaverse AI research directions (Huynh-The et al. 2023 ) a metaverse survey based on Blockchain and AI. Digital currencies, virtual AI, and Blockchain technologies are integrated into the paper. These components are examined to understand how Blockchain and AI interact with the Metaverse (Yang et al. 2022 ). This study examines three components to create an immersive Metaverse like Ready Player One, Roblox, and Facebook. The authors emphasize films, games, and studies. They discuss how these platforms improve user experience and virtual social interaction. They also list social influences, constraints, and open challenges that must be overcome to implement an immersive Metaverse (Park and Kim 2022 ).

5 Discussion

This section examines three critical features of the Metaverse literature: motivations, challenges, and recommendations to reduce these issues to improve Metaverse quality.

5.1 Motivations

The convergence of the Metaverse and AI is fueled by various variables, each of which offers up new possibilities, see Fig.  6 . For starters, Horizons: The Synergy of AI and Advanced Technologies in the Metaverse is emerging. AI, paired with current technology, enhances user experiences by enabling personalized interactions, realistic NPCs, and content creation, propelling the Metaverse to new heights of immersion and engagement. The second theme is transforming Education and Medical Training Through the Metaverse. AI-powered adaptive learning and simulations revolutionize educational and medical training circumstances by giving personalized experiences that improve learning outcomes and medical skill development. Finally, in Metaverse and IoT: A synergistic integration of cutting-edge technologies, AI connects the Metaverse and the Internet of Things, creating an interconnected environment that combines virtual experiences with physical devices, resulting in intelligent automation, efficient management, and seamless integration of the Metaverse’s digital and physical worlds. Together, these motivations propel the Metaverse and AI forward, promising a future in which virtual experiences are more rich, transformative and interconnected.

Metaverse motivations

5.1.1 Emerging horizons: the synergy of AI and advanced technologies in the metaverse

In recent times, significant progress in AI has allowed the development of innovative approaches and substantial enhancements in the provision of established services and applications. The Metaverse has emerged as a beneficiary of technical advancements (Rospigliosi 2022). AI-based metaverse technology has significant potential to provide valuable assistance to those afflicted with various mental disorders. For instance, individuals diagnosed with BPD have a notably heightened propensity for engaging in suicidal behaviours. Individuals that engage in suicidal behaviour often do so due to experiencing symptoms of depression, anxiety, and impulsivity. An AI-driven conversational agent, functioning as a virtual assistant or companion, might serve as a reliable source of support for individuals, offering them a constant presence to address and ease the sometimes burdensome emotions they experience (Ahuja et al. 2023 ). The Metaverse leverages AI and blockchain technology to create a digital virtual environment that facilitates social and economic interactions beyond the limitations of the physical world. The integration of these advanced technologies is expected to expedite its development (Mozumder et al. 2022).

Due to the swift advancement of deep learning technology recently, individuals have started using deep learning methods to address 3D human reconstruction endeavours. There are two main classifications for approaches: parametric techniques and non-parametric methods. The parameterization technique utilizes a deep learning algorithm to estimate the parameters of the 3D human model. Subsequently, the contour is modelled based on these parameters to get the reconstruction result (Su et al. 2022 ). The Metaverse’s construction involves several technological components, including network communication technology, Internet of Things technology, artificial intelligence, extended reality, virtual reality technology, and blockchain technology (Ding et al. 2022 ). Machine vision, an amalgamation of computer vision and extended reality (XR), is seen as a vital technological component in establishing the foundational structure of the Metaverse. Collecting and processing raw data from the visual world allows for the inference of high-level information.

This information is presented to users through head-mounted devices, smart glasses, smartphones, and similar devices (Huynh-The et al. 2023 ). The data inside the Metaverse has distinctive characteristics that enable its identification and use within a blockchain-based system, hence facilitating the traceability of such data. The resource in question has been identified as a valuable asset in machine learning (Tran et al. 2023 ). The increasing prevalence of Metaverse apps, including AR and VR, has facilitated the remote instruction of sign language via an avatar replicating human gestures. This avatar is driven by an AI-driven framework, enhancing both the accessibility and enjoyment of the learning process (Batnasan et al. 2022 ). AI with other technological advancements such as AR/VR, blockchain, and networking can potentially establish a metaverse that offers safe, scalable, and immersive virtual environments on a reliable and continuously accessible platform. Based on the seven-layer metaverse design, the significance of AI in ensuring infrastructure dependability and enhancing performance is unquestionable (Huynh-The et al. 2023 ).

5.1.2 Transforming education and medical training through the metaverse

In order to address the disparities in learning within traditional educational settings, implementing an educational metaverse has the potential to provide a customized and distinctive learning environment and encounter. Additionally, it may give a personalized learning and development strategy that considers each student’s individual psychological attributes and cognitive processes. Integrating virtual and physical digital learning environments and using interactive learning methods developed by the educational Metaverse is expected to significantly enhance students’ desire to engage in the learning process (Lin et al. 2022 ). From an industrial perspective, the primary application scenario of the metauniverse is education. This statement emphasizes the conceptualization of education as a societal effort to promote individual growth throughout one’s lifespan and underscores the incorporation of technology into future educational systems. The emergence of the education metauniverse is poised to become a viable model for addressing the intersection of technological progress and educational obstacles (Sun 2022 ). The advent of the meta-universe era has considerably expanded the range of network activities college students show. The author posits that college students possess distinct characteristics in their engagement with network entertainment and network socialization, which align with their age and interests in online activities.

Consequently, the author proposes categorizing these behaviours into five primary dimensions: network learning behaviour, network social behaviour, network entertainment, network consumption behaviour, and network expression behaviour. These divisions are based on shared objectives and motivations (Ge 2022 ). Extended reality technology has significant promise in shaping the landscape of medical education in forthcoming years. The expanding range of applications for this technology may be used across all phases of the medical training process. The examination and discourse around these applications are of utmost importance in guaranteeing our medical education system’s future advancement and holistic proficiency (Ahuja et al. 2023 ). The use of augmented reality within the healthcare industry has a notable influence on prospective healthcare professionals’ competencies and knowledge foundations. Surgical aiding tools, such as the Microsoft HoloLens, are technological devices surgeons use to enhance and expedite surgical operations (Mozumder et al. 2022).

5.1.3 Metaverse and IoT: a synergistic integration of cutting-edge technologies

Integrating the Internet of Things (IoT), technology plays a pivotal role in the metaverse ecosystem. Internet of Things (IoT) devices facilitate the transmission of gathered data to higher-level applications, allowing instantaneous communication and fostering immersive experiences inside the Metaverse (Ding et al. 2022 ). The Metaverse is a novel application with significant gains due to technological advancements. The Metaverse relies heavily on data manipulation due to the integration of several advanced technologies, such as the IoT, DT, and big data (Rospigliosi 2022). The concept of the Metaverse and the IoT might be seen as digital twins, with the Metaverse being characterized by higher use of IoT devices inside its virtual office environment. The data in question has a distinct identifying tag and serves as traceable information inside the blockchain-based Metaverse (Mozumder et al. 2022). The global interest in the Metaverse has increased due to the emergence of IoT, virtual reality, cloud computing, and digital twin technologies. The Metaverse platform incorporates and utilizes several developing technologies in cloud education, smart health, digital governance, and disaster relief (Gu et al. 2023 ). The Metaverse provides a wide range of persons with extended network connectivity through wireless networks. In the last decade, several innovative technologies have been developed to enhance the overall efficiency of wireless communication and networking systems. AI has been extensively integrated into different layers of network design (Huynh-The et al. 2023 ).

5.2 Challenges

The ethical considerations of implementing various technologies and applications pose a significant challenge within the metaverse framework. Ensuring the safeguarding of user assets and maintaining the privacy and security of data is of paramount significance. Moreover, it is crucial to recognize and address the economic obstacles and technical complexities to fully realize the immersive metaverse experience’s extensive potential. Applying advanced technologies, such as DRL and electronic stickers for body measurement, poses challenges concerning reliability, accuracy, and user experience. Analyzing user satisfaction and resolving complex interactions between manipulation types, object properties, and user preferences present considerable challenges in advancing immersive and realistic metaverse applications (Fig. 7 ).

Metaverse challenges

5.2.1 3D modelling, rendering, and interaction

The development of the Metaverse and VR technology has posed significant challenges for 3D research, including 3D modelling, rendering, interaction, collaboration, and ethical considerations (Fan et al. 2022 ). Accurate 3D human body modelling in the Metaverse is challenging, especially for capturing detailed facial textures. A proposed solution combines a 3D reconstruction algorithm with facial features. Using a 3DMM, the algorithm predicts facial parameters and extracts features. These are then fused with 2D image features, enhancing accuracy. Challenges include body proportions, appearance variations, real-time performance, privacy, user customization, cross-platform compatibility, and ethical considerations. This approach improves 3D modelling for realistic virtual representations (Su et al. 2022 ).

5.2.2 Ethical considerations

One of the challenges in implementing the proposed metaverse network intrusion detection model is addressing the complexity and scalability issues that arise due to the integration of multiple technologies, such as GAN, IoT, DAE, and RF, while ensuring efficient and accurate detection of abnormal traffic in the Metaverse (Ding et al. 2022 ). Challenges in implementing the immersive Metaverse include ethical considerations, economic barriers, and technical hurdles (Park and Kim 2022 ). However, the implementation of DRL technology in emergency evacuation systems using the Metaverse also presents particular challenges, such as ensuring the reliability and accuracy of real-time data collection, addressing potential privacy concerns related to sensor data, and optimizing the DRL model to handle complex and dynamic evacuation scenarios effectively (Gu et al. 2023 ).

Developing a skin-interactive electronic sticker for measuring body curvature and skin wave fluctuations poses several challenges, including ensuring high detection sensitivity, accurate image segmentation, robust deep learning algorithms, compatibility with different body types, and establishing the reliability and usability of the device in various wearable applications (Hong et al. 2022 ). The challenges in studying satisfaction with virtual object manipulation in MR-based metaverse applications include understanding the complex interplay between manipulation types, object properties, and user preferences and ensuring seamless integration of MR technology to provide an immersive and realistic experience for users (Choi and Kim 2022 ). Integrating meta bots with motion capabilities into complex virtual 3D worlds and optimizing their behaviour through an evolutionary computation-based learning model presents challenges such as navigating intricate environments, achieving realistic human-like behaviours, managing the optimization process, balancing exploration and exploitation, ensuring generalization to diverse scenarios, integrating with social networks, and addressing ethical considerations. Overcoming these challenges is crucial for enhancing meta bots’ capabilities and seamless integration in virtual environments (Arroyo et al. 2011 ). The challenges associated with AI in the Metaverse for educators include navigating data privacy and security issues, addressing biases and discrimination in AI algorithms, preserving learner autonomy and agency, and promoting ethical AI design principles (Rospigliosi 2022).

5.2.3 Metaverse network and security

Blockchain implementation in the metaverse environment is complex. First, the Metaverse’s dynamic AI-based services need blockchain to be adaptive. Smart contracts and consensus methods may suffer in a fast-paced environment. The Metaverse creates and analyzes massive quantities of data, making scalability a challenge. Blockchain must effectively manage massive transaction volumes and data storage. Metaverse ecosystem security is essential. The Metaverse manipulates massive volumes of data, making data integrity, privacy, and secrecy challenging to maintain. Blockchain implementation should address these security concerns effectively to build trust and confidence within the Metaverse (Bouachir et al. 2022 ). Securing the Metaverse is challenging due to the need for seamless integration of real and virtual elements while ensuring robust security. Hacker attacks exploiting anonymous texts pose a significant risk, requiring safeguarding user assets. Leveraging NLP technologies like TF-IDF, word2vec, GRU, RNN, and LSTM aids content analysis and anomaly detection. Optimizing algorithms for metaverse security, including topic extraction and grouping, is crucial. Ongoing research focuses on validating algorithm performance and overcoming limitations for a practical approach (Park et al. 2022 ).

5.2.4 Immersive metaverse implementation

The challenges in human–machine interactions using current interactive sensing interfaces include massive crossover electrodes, signal crosstalk, propagation delay, and demanding configuration requirements (Wei et al. 2022 ). Introducing XIVA as an intelligent voice assistant for the educational Metaverse presents challenges in integration, infrastructure, language processing, privacy, testing, and ongoing support (Lin et al. 2022 ). Challenges in gesture recognition systems and wearable devices for human–machine interfaces include limited sensor data quality, high computational costs, difficulty in differentiating gestures, establishing correspondence between muscle/tendon groups and gestures, optimizing models with reduced computational resources, achieving low latency for real-time operations, and enhancing cyber-human interactions (Fang et al. 2022 ). The challenges in finger vein recognition for the Metaverse include low-quality images, variations in contrast, scale, translation, and rotation, as well as the need for robust security against unauthorized access and data compromise (Tran et al. 2023 ). While technology development to facilitate communication for people with hearing loss is promising, several challenges remain to address. These challenges include the limited availability of datasets and resources for Arabic sign language compared to other languages, the need for accurate and reliable gesture recognition algorithms, and ensuring widespread access to the developed systems and applications. Additionally, variations and regional differences in sign language may need to be accounted for in the development process. Overcoming these challenges will be crucial for creating compelling and inclusive solutions for the deaf and hard-of-hearing community (Batnasan et al. 2022 ).

5.2.5 AR/MR and VR

AR/MR audio implementation faces challenges in latency management, including fast head tracking, lightweight DL models, training data sets, strict latency in real sound control, acceptable latency in virtual sound rendering, hardware limitations, and efficient filtering methods (Gupta et al. 2022 ). The study faces challenges in accurately distinguishing and interpreting emotional states based on EEG signals in the context of AR-based reading. Additionally, ensuring the generalizability of the findings beyond the specific stimuli used and addressing potential confounding factors are important considerations. Furthermore, integrating AR systems into various Metaverse-based applications may require overcoming technical and practical hurdles for widespread adoption (Daşdemir 2022 ). VR’s challenges include wealth inequity due to high costs, algorithmic bias in data processing, digital exclusion for those without access, limited policy engagement, and the need for regulatory intervention (Egliston and Carter 2021 ). The challenges in metaverse construction include high model complexity, computational efficiency, local and global feature representation, and providing clear semantic information for objects. The CWCT transformer framework addresses these challenges by combining CNN and transformers, optimizing Cross-Window Self-Attention for local features and utilizing CNN for global features. It improves classification accuracy and operation speed and reduces model complexity compared to the original CMT network (Li et al. 2022a , b , c ). Designing a deep learning-based asymmetric virtual environment presents challenges in gesture recognition, hand tracking, text recognition, seamless integration, user satisfaction, system performance, and user adaptation. Overcoming variations in gestures and hand tracking accuracy, interpreting handwritten text, integrating VR and AR seamlessly, ensuring user satisfaction and immersive experiences, optimizing system performance, and aiding user adaptation are crucial considerations in this design process (Cho et al. 2022 ).

5.2.6 Metaverse AI gesture recognition challenges

Implementing intelligent non-contact gesture recognition systems faces several challenges. These include the need to ensure high accuracy across diverse user populations, accounting for variations in lighting and real-world conditions, accommodating a wide range of diverse and complex gestures, optimizing user experience and ergonomics, addressing scalability and integration with different platforms and devices, and addressing data privacy and security concerns associated with collecting and processing user data (Zhou H et al. 2022 ). The challenges in the proposed project include technical complexity, user adaptation, accessibility, content creation and management, connectivity and infrastructure, assessment and evaluation, cost and scalability, and privacy and security (Sghaier et al. 2022 ).

5.3 Recommendations

The recommendations in Fig.  8 focus on four key areas regarding which policy is required to achieve the general vision for Metaverse and AI, which are outlined next.

Metaverse recommendations

5.3.1 Sensor data

The acquisition of real-time data from diverse real-world components is a crucial resource for developing superior services in metaverse applications based on the IoT (Bouachir et al. 2022 ). Touchless HMIs have gained significant traction recently due to their notable benefits in superior hand dexterity, enhanced comfort, and improved hygiene. Consequently, they have great potential in several domains, such as intelligent robotics, virtual and augmented reality, and medical facilities (Zhou et al. 2022 ). The surface charge effect enhances the sensor array’s ability to detect muscle/tendon activity with superior reliability, sensitivity, and cost-effectiveness compared to the conventional surface electromyography (sEMG) technique. Significantly, the strong correlation between the activity of the dominant muscle/tendon groups and gestures plays a crucial role in distinguishing various components in sensor data, potentially enhancing the accuracy of gesture categorization. The analysis of the collected data from different hand gestures reveals the exceptional robustness and consistency of the sensor system. Additionally, a correlation is identified between the patterns of signal waveforms and the motions of significant muscles and tendons (Fang et al. 2022 ). The AIOM touch sensor exhibited a notable regional diversification in its mechanosensitive signal, enabling it to effectively react to both single-point touch sites and multipoint touch positions in the presence of spatiotemporally dynamic mechanical stimulations (Wei et al. 2022 ). Combining 3D virtual worlds with social networks provides software agents with similar attributes to avatars controlled by humans (Arroyo et al. 2011 ). Recent regulatory developments regarding data provide valuable insights into managing VR as a technology that generates substantial data. The FTC in the United States has lately directed its attention to the data used in face recognition algorithms. The FTC has issued a directive mandating the cessation of operations for algorithms developed using unlicensed data, specifically photographs obtained via unauthorized means from social media platforms. A comparable approach might be employed to mitigate the possibility for Facebook to exploit and re-identify VR data (Egliston and Carter 2021 ).

5.3.2 Data pre-processing

The efficiency of pre-processing and post-processing activities has been improved. The relevance of AR stimuli is seen in both the beta and gamma frequency bands in the categorization of 2D-VA groups. In the context of the 2D-VA group, it was shown that AR stimuli were more suitable for portraying emotional states. Previous research has shown the efficacy of including valence and arousal aspects (Daşdemir 2022 ). During our security strategy investigation aimed at mitigating hacker assaults, we saw that implementing filtering mechanisms proved very beneficial in several aspects, including subject classification, identification of risky groups, dimension management, and token classification methods (Park et al. 2022 ). Given that the frames extracted from the in-house video have not been included in any of the existing datasets, it would be justifiable to conduct a comparative analysis of two models in terms of their performance in classifying indicators that have been removed from the in-house video, using annotated frames as reference (Batnasan et al. 2022 ). The production of a stereoscopic effect necessitates the employment of display technology since a minimum of two images with distinct viewing angles is required for a comprehensive 3D stereoscopic image (Fan et al. 2022 ). To enhance the performance of the intrusion detection model, it is necessary to address the need for improvements in both model stability and timeliness (Ding et al. 2022 ).

5.3.3 Metaverse construction

Providing specific semantic information for each item is critical to improving interaction throughout the metaverse development process (M. Li et al. 2022a , b , c ). When an AR user is exploring and experiencing the general virtual world, he or she may use the text interface to interact with the virtual environment and other users and perform other mode transition activities (Cho et al. 2022 ). The interaction in the Metaverse is built on virtual three-dimensional space, which includes virtual landscapes, virtual characters, and so on. As a consequence, technological advances in three-dimensional human body reconstruction have had a profound impact on the Metaverse (Su et al. 2022 ). Natural and continuing interactions between people and XR devices are essential in the developing metaverse age. However, present rigid wearable devices are large, heavy, and costly (X. Zhang et al. 2022a , b ). Use the metaverse-based evacuation strategy in various situations, such as buildings with complex floor plans, evacuees in wheelchairs, or falls during the evacuation operation. All of this adds to the challenges of the evacuation (Gu et al. 2023 ).

Future educational metaverse development objectives include creating a new generation of talent with immersive "listening, speaking, reading, and writing" literacy skills. Simultaneously, the critical objective of constructing the future educational Metaverse is to provide virtual teachers or learning aides with the essential abilities of "listening, speaking, reading, and writing" (Lin et al. 2022 ). Computers and mobile phones are only two ways to connect to the Metaverse.

However, these gadgets do not give the same level of interaction as actual metaverse devices. Virtual reality equipment (Google, Samsung, HTC Vive, etc.) provides the most immersive experience (Tran et al. 2023 ). The small and portable device will provide a more user-friendly and intuitive UI solution than those now available in the Metaverse. Consequently, it will hasten the transition to a pandemic-induced touchless interface society (Hong et al. 2022 ). Disabled students may have easier access to more diversified tools to help them engage with the 3D virtual world. Indeed, instructors and students will no longer need to be physically present in the classroom or even in the same country for learning, assessments, and exams. Consequently, people may be able to access these experiences in the Metaverse as avatars (Sghaier et al. 2022 ). Despite much research into the Metaverse, the focus has been chiefly on social meaning, with little attention made to Metaverse technology. A rigorous approach to what concepts and technologies are needed to create an environment and material that consumers can appreciate, such as in Ready Player One (Park and Kim 2022 ), is required. The MRMA’s object manipulation significantly impacted user satisfaction (Choi and Kim 2022 ).

5.3.4 Metaverse developers

The comprehension of AI decision-making processes, such as the generation of predictions by AI models, is likely to need to be completed for metaverse developers, virtual world designers, and users, leading to a reliance on these processes without a comprehensive understanding of their inner workings. XAI refers to a comprehensive set of tools and methodologies utilized to define AI models, evaluate their anticipated outcomes, describe the transparency of the models, and scrutinize the results. These tools and methodologies facilitate human users in comprehending and placing trust in AI models by monitoring the entire process and ensuring accountability (Huynh-The et al. 2023 ). As the Metaverse continues to gain popularity, there is a corresponding increase in our dependence on artificial intelligence. As a result, teachers may encounter various formidable challenges. This editorial will elucidate many rationales for individuals using interactive learning settings to exercise caution while first navigating the Metaverse.

In order to adequately highlight these issues, it is necessary to provide a clear definition of the Metaverse, including the technology it employs and its potential applications in an educational environment (Rospigliosi 2022). The use of extended reality technology in healthcare delivery has raised concerns over the depersonalization of medicine. Providing substantial evidence for the comparable efficacy of digital and physical modes of human connection is challenging now, mainly owing to the nascent stage of extended reality and metaverse advancements. Currently, the predominant area of research pertaining to extended reality technology is its use in medical education. Nevertheless, the specific implications of using this technology in interpersonal interactions between physicians and patients remain uncertain and require more investigation (Ahuja et al. 2023 ).

6 Analysis of characteristics and research gaps

This section will look at various critical factors that will help academics by addressing gaps in future research. Each component draws attention to a gap in the research literature and examines the missing ingredient or elements. Because the Metaverse has not been adequately researched, it must be explored. The subsections that follow, on the other hand, include several essential numbers and research that explain the current state-of-the-art Metaverse.

6.1 The reality of applying trustworthy AI requirements in metaverse studies

Several recent discussions have focused on the transparency of AI-based solutions. This is understandable, given that some of these algorithms are black boxes, demonstrating how difficult it is to articulate their inner workings. Furthermore, since this technology is based only on historical and often human-generated data, it may sometimes exhibit various types of bias, creating ethical difficulties. Now that AI-based solutions are widely used in medical devices, fairness, ethics, transparency, and reliability are indispensable. The seven elements of trustworthy AI have been discovered.

These components include human agency and supervision, technology robustness and safety, privacy and data governance, transparency, diversity, non-discrimination and fairness, social and environmental well-being, and accountability. It should be noted that the word "trustworthy AI" implies that the authors are concerned with ensuring that the AI used in Metaverse applications of taxonomy literature is reliable, safe, and ethical. Given the potential impact of AI on Metaverse system outcomes, this is an important subject. As a consequence, Table (1) depicts the presence of reliable AI criteria in Metaverse literature. The authors may have researched several publications in various fields of literature and identified the most often stated conditions for trustworthy AI. According to EU legislation, there are seven key criteria for trustworthy AI (see Fig.  9 ). The seven critical aspects of AI governance can be summarized as follows: First , human agency and oversight involve safeguarding fundamental rights, involving human decision-making, and ensuring human supervision. Second , technical robustness and safety encompass protection against security threats, backup plans for system failures, and maintaining accuracy and reliability. Third , privacy and data governance focus on upholding data quality, privacy, and access. Fourth , transparency entails tracing and clarifying decision-making processes and communicating outcomes transparently to stakeholders. Fifth , diversity, non-discrimination, and fairness encompass preventing biased outcomes, ensuring inclusivity and accessibility, and promoting stakeholder involvement. Sixth , societal and environmental well-being considers sustainability, social and environmental impact, and democratic values. Lastly , accountability involves audibility, mitigating and reporting negative consequences, acknowledging trade-offs, and providing necessary remedies.

The seven essential elements of trustworthy AI

The significance of all seven demands is noteworthy as they mutually enhance each other, and it is imperative to implement and assess them over the whole lifespan of the AI system (Wei and Liu 2024 ; Alzubaidi et al 2024a , b , c , d ). When evaluating criteria in various domains and sectors, it is essential to consider the contextual factors and any conflicts that may arise. These criteria have to be used throughout the whole life cycle of an AI system and should be subject to variation depending on the specific application.

The bulk of the criteria apply to all AI approaches, with particular emphasis placed on those that have a discernible influence, whether direct or indirect, on individuals. Consequently, specific applications, particularly those in industrial contexts, may see a decrease in relevance. Under some conditions, the existing statute already encompasses the abovementioned requirements. In accordance with the first element of reliable AI, AI professionals are responsible for adhering to their legal obligations, including universally applicable norms and regulations unique to their respective fields. Moreover, the term ‘trustworthy AI’ indicates the authors’ focus on ensuring the reliability, safety, and ethicality of the AI used in the Metaverse. The significance of the subject matter lies in the prospective consequences of AI on the results of Metaverse applications. Table 1 presents the prevalence of reliable AI requirements in the existing literature on the Metaverse. The researchers extensively reviewed the current body of literature on the Metaverse in order to find the prevailing conditions often cited for ensuring the trustworthiness of artificial intelligence.

Based on an examination of several sources, Table  1 illustrates that the prevalence of trustworthy AI needs to be provided in Metaverse literature. For each reference, the Table shows the frequency of each need as very low (VL), low (L), medium (M), high (H), or very high (VH). The following sections provide the debate and analysis for each requirement:

In the Metaverse literature, the percentages of Human agency and oversight required are VH (0%), H (0%), M (0%), L (0%), and VL (100%). According to the literature reviewed, all research or papers on Metaverse need 100% human oversight and agency. This suggests that no autonomous Metaverse systems in the literature run without human input or supervision and that all systems need some degree of human control. This might be owing to the fact that the Metaverse is still in its early stages and completely autonomous systems do not yet exist, or it could be due to ethical issues, technological limits, or safety concerns. It should be noted that this assertion is particular to the material reviewed and may not reflect the whole area of Metaverse. The degree of human agency and oversight necessary in these systems may alter as Metaverse technology progresses and new research is undertaken.

In terms of technological robustness and safety, the investigations meet this need in the following percentages: VH (10%), H (18%), M (32%), L (10%), and VL (30%). According to the percentages, the majority of research addresses this need as M, with VH and H being the least represented. Although Metaverse is meant to be technically robust and safe, only some researchers deem this need important or high-risk.

Based on the percentages, it seems that the Metaverse system under consideration puts a low value on the "Privacy and data governance" criteria. Specifically, all studies thought this need was insignificant, and just 8% thought it was crucial. Furthermore, 22% of the studies thought it was of medium relevance, while 16% thought it was of low value. The majority of research (54%) rated it as extremely low relevance. This shows that the Metaverse system may need more comprehensive privacy and data governance controls and that it may prioritize user data protection and compliance with applicable data privacy laws and regulations. This might be a problem for businesses or people using the Metaverse system, mainly if dealing with sensitive or secret information. Exploring new privacy and data governance procedures may be necessary to address these concerns to enhance the Metaverse system’s capabilities.

VH criteria are not reflected in the "Transparency" criterion, whereas the bulk of the requirements (78%) fall into the VL group. Furthermore, 14% of the studies regarded it to be of considerable relevance, compared to 2% and 6% for the H and L needs, respectively. This implies that the Metaverse system emphasizes openness for low-risk needs, but high-risk requirements may get less information. However, it is crucial to emphasize that more details of the precise standards and their execution are necessary to properly assess the efficiency of the existing transparency measures.

Based on the percentages, it seems that the Metaverse system under consideration puts a low value on the "Diversity, non-discrimination, and fairness" criteria. In particular, none of the research deemed it to be of very high or high relevance. Furthermore, 8% of the studies thought it was of medium relevance, while 18% thought it was of low value. The majority of research (74%) rated it as extremely low relevance. This shows that the Metaverse system may not prioritize encouraging diversity, equality, and inclusion in its outputs and ensuring that its models are not prejudiced against certain groups of people. This may be a source of worry for organizations or people using the Metaverse system, mainly if they operate in industries where fairness and non-discrimination are essential. Additional methods may be necessary to examine and eliminate biases in the Metaverse system’s outputs or enhance its capabilities with tools or procedures that promote fairness and non-discrimination.

The percentages supplied for the "Societal and environmental well-being" criteria indicate that the Metaverse system under consideration puts a very low value on this need. In particular, none of the studies judged this condition to be extremely important, and just 2% of the studies considered it to be essential. Furthermore, 24% of the studies thought it was of medium relevance, while 14% thought it was of low value. The majority of research (60%) rated it as extremely low relevance. This implies that the Metaverse system may not prioritize the possible consequences of its outputs on society and the environment. This may be a source of worry for organizations or people using the Metaverse system, mainly if they operate in domains where societal and environmental well-being are essential, such as sustainable development or social justice. Additional actions may be required to examine and mitigate the negative implications of the Metaverse system’s outputs on these sectors.

The "Accountability" criteria percentages indicate that the Metaverse system under consideration puts a relatively low weight on this need. None of the studies thought it was of very high, high, or medium relevance, and just 2% thought it was of low value. The bulk of research (98%) rated it as extremely low relevance. This implies that the Metaverse system may not prioritize guaranteeing openness and accountability in its processes and outputs. This might worry companies or people that use the Metaverse system, mainly if they operate in highly regulated sectors or disciplines. Additional actions may be necessary to promote openness and accountability, such as developing auditing or documentation procedures to monitor the system’s inputs and outputs.

This shows that the Metaverse literature still needs to incorporate these characteristics of trustworthy AI completely. Diversity, non-discrimination, and justice are similarly relatively low on the list, with only a few sources rating them as high or extremely high. This is especially important in light of the rising awareness of prejudice and discrimination in AI systems and the need for more inclusive and fair AI development. Overall, the Table demonstrates that the most often cited characteristics of trustworthy AI in the Metaverse literature are technological robustness and safety, human agency and supervision, and privacy and data governance, with very high or high scores in many studies. On the other hand, diversity, non-discrimination and justice, social and environmental well-being, and accountability are less commonly cited, with primarily medium or poor scores. It should be noted that the findings in the Table represent the emphasis of the examined research, not the overall value or usefulness of each feature of trustworthy AI in the creation of Metaverse systems.

6.2 Metaverse datasets for AI applications

In general, AI techniques and datasets are critical. The main focus of the study is the availability of reliable Metaverse datasets for use in AI applications. The employment of AI in the Metaverse has great potential for improving user experience, speeding data processing, and strengthening security measures. Here’s a more in-depth look at how AI may directly help in these areas (Otoum et al. 2024 ; Soliman et al. 2024).

Improved User Experience:

Personalisation: AI algorithms analyse user behaviour, preferences, and interactions in the Metaverse to deliver personalised experiences. For example, AI may adjust virtual surroundings, avatars, and content suggestions to individual interests, increasing user engagement.

Natural Language Processing (NLP): AI-powered chatbots and virtual assistants can let people communicate seamlessly with the Metaverse. NLP allows these assistants to interpret and reply to natural language questions, assisting users with navigation, information retrieval, and task completion.

Immersive Interactions: AI may improve immersion by creating realistic simulations, dynamic surroundings, and lifelike NPCs (non-player characters) in the Metaverse. This results in more engaging and dynamic experiences for users, encouraging deeper relationships and longer engagement.

Optimising Data Processing:

Big Data Analytics: The Metaverse creates large volumes of data via user interactions, transactions, and virtual environments. AI-powered analytics can effectively handle large amounts of data to provide important insights such as user behaviour patterns, market trends, and performance indicators. These insights may help with decision-making, content optimisation, and personalised suggestions.

Predictive Modelling: AI algorithms may utilise previous data to forecast future trends, user preferences, and possibilities in the Metaverse. This allows proactive decision-making, resource allocation, and content curation to accommodate changing user needs and market realities.

Real-time Processing: Artificial intelligence enables real-time data processing and analysis, allowing for dynamic changes and optimisations inside the Metaverse. This assures reactivity, scalability, and adaptation to changing situations, resulting in better user experiences and increased operational efficiency.

Improved Security:

AI-powered security systems identify and mitigate cyber risks including malware, phishing attacks, and unauthorised access in the Metaverse. Machine learning algorithms can proactively detect possible security breaches by analysing trends and abnormalities in user behaviour, network traffic, and system activity.

Fraud Prevention: Artificial intelligence can improve fraud detection and prevention by analysing transactional data, user profiles, and behavioural patterns for signals of suspect or fraudulent conduct. This helps to protect financial transactions, virtual assets, and sensitive data inside the Metaverse.

Content Moderation: Artificial intelligence algorithms may automate content moderation procedures by recognising and filtering out improper or harmful information, such as hate speech, harassment, or explicit material. This provides a safer and more inclusive virtual environment for users, hence reducing possible risks and liabilities.

To summarise, the integration of AI technology has enormous potential to convert the Metaverse into a more immersive, efficient, and secure digital environment, providing improved user experiences while tackling difficult data processing and cybersecurity concerns. Furthermore, most authors do not share and keep their information secret for various reasons, exacerbating availability difficulties. Journals regularly require dataset disclosures to be included in published research. This means the datasets presented inside the publications must meet all legal criteria. In contrast, more specific datasets generated for risk bias concerns and solutions are becoming a significant concern. Consequently, further research should be conducted to improve the trustworthiness of AI systems by employing relevant datasets produced for risk bias concerns and solutions. Table 2 includes crucial information on dataset availability, a description, size, or sample of the data, and how large data has been handled in the AI trustworthiness study.

The paragraph describes a diverse set of datasets used across various domains. It includes datasets for human scans showcasing clothing, body shapes, and poses for computer vision applications. There are datasets for network traffic (normal and attack) used in network security and intrusion detection research. Other datasets include sensor technology, email classification, keystroke data, Chinese voice, hand motion, finger biometrics, multimodal biometrics, sign language recognition, EEG data for emotion recognition, and image classification benchmark (MNIST). There are also datasets for gesture recognition and disabled learners in a 3D virtual environment for inclusive education and virtual reality research. The case studies in the dataset description column received minimal attention in the study. The dataset settings used in the literature were mainly focused on images, signals, words, and packets. When the third and seventh columns in Table  2 are compared, it is feasible to conclude that despite having a small sample size, some studies considered their datasets significant. It should be noted that datasets including just 22 people’s EEG signals, as in (Dasdemir 2022 ), or 1000 photos, as in (Li et al. 2022a , b , c ), were considered big data. One potential source of worry is that some researchers may use the term ‘big data’ as a buzzword to make their work sound more impressive, even if it still needs to meet the established qualifications for big data. This might be owing to the excitement around big data, which has led to misunderstandings about what it comprises. be a consequence, detailed reasons for why a dataset is referred to be big data are required, taking into consideration not just the collection’s size but also its complexity, variety, and velocity. This may help ensure that research initiatives are credible and adequately labelled and provide clarity among academics and policymakers about what constitutes big data. Furthermore, although all of the authors in the relevant study declared that the datasets used satisfied the legal standards, numerous publications omitted a link to data availability. Researchers must adhere to regulatory obligations while collecting, processing, and exploiting data, particularly given the rising focus on data privacy and security. This includes following data protection norms and regulations such as the EU’s GDPR, the Accountability Act in the US, and analogous legislation worldwide (Fig. 10 ).

Topic modelling of AI in metaverse

The diagram depicts a thorough topic modelling for classifying research papers on the Metaverse and its uses. The taxonomy is divided into six main groups, each of which covers a particular subject topic as follows:

Human Engagement and Interaction in the Metaverse

Measuring People Engagement (Park and Kim 2022 ).

Using Speech Interactions with Virtual Objects in Mixed Reality (Siyaev and Jo 2021).

User Satisfaction with Virtual Object Manipulation in Mixed Reality (Choi and Kim 2022 ).

Deep Learning-based Interaction Recognition and Sensor Applications (Wei et al. 2022 ).

Development of an Intelligent Voice Assistant (Lin et al. 2022 ).

Gesture Recognition System using Smart Wristbands (Fang et al. 2023 ).

Deep Learning-based Gesture and Text Interfaces in an Asymmetric Virtual Environment (Cho et al. 2022 ).

Intelligent Noncontact Gesture-Recognition System for Medical Applications (Zhou H et al. 2023 ).

Optimization and Control Algorithms for Metaverse Applications

Evolutionary Computation for Optimizing Fuzzy Controllers (Arroyo et al. 2011 ).

Hierarchical Multiagent Reinforcement Learning Approach with Experience (Hare and Tang 2022 ).

Hybrid Intrusion Detection Model using GAN, DAE, and RF (Ding et al. 2022 ).

Deep Reinforcement Learning for Emergency Evacuation in the Metaverse (Gu et al. 2023 ).

Technological Innovations and Applications

Fusing Blockchain in Metaverse Applications (Yang et al. 2022 ).

Hybrid Cartridge Format Electronic Sticker for Body Analysis and Control (Hong et al. 2022 ).

Finger Vein Recognition for VR Human–Robot Equipment (Tran et al. 2023 ).

Arabic Sign Language Gesture Recognition for Enhanced Accessibility (Batnasan et al. 2022 ).

Improved Image Classification Framework for Metaverse Construction (M. Li et al. 2022a , b , c ).

Ethical and Societal Implications of Metaverse and Virtual Reality

Ethical Issues in Metaverse and Deep Learning-based Interactive Experiences (Rospigliosi 2022).

Data-Borne Harms and Power Inequities in Virtual Reality (Egliston and Carter 2021 ).

Education and Learning in the Metaverse

Propositions of Metaverse Tourism (Koo et al. 2022 ).

AI-based Methods for the Metaverse: NLP, Machine Vision, Blockchain, Networking, Digital Twin, Neural Interface (Huynh-The et al. 2023 ).

Signal Processing Techniques for AR/MR Audio in Educational Contexts (Gupta et al. 2022 ).

Emotion Recognition in AR Systems for Educational Activities (Daşdemir 2022 ).

Integration of Virtual Reality and Educational Technology

Virtual Learning Environment Integration with Educational Technology (Sghaier et al. 2022 ).

6.3 Evaluation and benchmarking process of the metaverse ecosystem

This section presents a proposed grouping algorithm to ensure the evaluation and benchmarking of topics pertaining to the Metaverse. The application of MCDM can be utilized to assess the efficacy of the Metaverse under consideration. This evaluation involves the consideration of various criteria, including but not limited to technical performance, user experience, content quality, ethical considerations, societal impact, performance metrics, security and safety, and accessibility. The proposed decision matrix for this process is shown in Table  3 .

The MCDM model can facilitate evaluating Metaverse performance concerning other established methodologies, thereby enabling the selection of optimal Metaverse strategies based on the identified criteria. Additionally, MCDM algorithms can provide an appropriate weight for the eight Metaverse criteria through the analytic hierarchy process (AHP) (Al-Qaysi et al. 2023 ) and best–worst method (BWM) (Rezaei 2015 ) that have shown promising results. However, the inconsistency in their weighing techniques needs to be addressed (Al-Humairi et al. 2022 ; Al-Samarraay et al. 2022b , a ; Albahri et al. 2022 ; Alsalem et al. 2022 ; Alzubaidi et al. 2024; Salih et al. 2021 ). To tackle this, FWZIC method has been introduced (Alsalem et al. 2021 ; Alamoodi et al. 2022 ). FWZIC method assigns weights to evaluation Metaverse criteria while ensuring zero inconsistency. It computes and calculates weight coefficients for each criterion separately, allowing for consistent and accurate assessment. By utilizing the FWZIC method or similar approaches, the evaluation and benchmarking of Metaverse can be performed more effectively. This method ensures that the weighting process is reliable and free from errors or inconsistencies that could impact the overall evaluation results. Furthermore, in the context of benchmarking issues and ranking, MCDM can be employed to address these challenges using the FDOSM (Alsalem et al. 2021 ; Al-Samarraay et al. 2022b , a ). FDOSM is a method used to determine the best rank for Metaverse alternatives, overcoming the issues associated with Metaverse criteria. FDOSM incorporates the concept of an ideal or optimal solution, eliminates inconsistency and two preferences, reduces the number of comparisons required, provides fair and implicit comparisons, and requires fewer mathematical operations (Alamoodi et al. 2022 ; Albahri et al. 2023 ). It also addresses concerns about normalization and weights, which are common in MCDM techniques. One of the critical features of FDOSM is its ability to handle ambiguous and fuzzy data. By employing these processes, FDOSM can effectively deal with imprecision and uncertainty in decision-making (Mahmoud et al. 2022 ). The advantage of utilizing this new combination lies in its ability to select the optimal or best Metaverse based on eight criteria. This method considers the overall performance of the Metaverse alternatives and incorporates a comprehensive evaluation based on multiple criteria, enabling the selection of the most suitable Metaverse. The FDOSM provides a systematic and robust approach to selecting the optimal Metaverse alternative by considering eight criteria and addressing the challenges associated with benchmarking and ranking in MCDM. Moreover, the utilization of MCDM can be advantageous in identifying potential trade-offs and conflicts that may arise among various dimensions within the Metaverse. One potential trade-off that can arise is balancing the degree of security and the level of user-friendliness or between the preservation of privacy and the extent of functionality. By thoroughly examining these trade-offs, individuals in positions of authority can arrive at well-informed decisions and achieve a suitable equilibrium among various criteria, considering the distinctive demands and limitations of the Metaverse setting. In conclusion, using MCDM to evaluate the proposed grouping algorithm for safeguarding Metaverse topics offers a methodical and unbiased appraisal of its efficacy. This aids decision-makers in making well-informed choices and improving the overall Metaverse ecosystem.

6.4 AI methods and techniques used in metaverse

As the Metaverse continues to evolve, AI plays an essential role in shaping and enhancing the immersive experiences within this virtual world. Thus, AI in the Metaverse has gained much attention recently as researchers employ AI solutions to create interactive virtual worlds. Table 4 provides a comprehensive overview of various research studies in AI regarding the Metaverse. It includes AI directions, methods used, metrics employed, applications, and technologies such as AR, VR, IoT, NLP, Computer Vision, Machine Learning, GANs, Reinforcement Learning, Virtual Assistant Technology, Semantic Web, Multi-agent Systems, NLG, Predictive Analytics, and Computer Graphics.

Table 4 highlights different research areas or directions of AI in selected papers and their respective AI applications. For example, face detection and landmark identification using MTCNN are explored in the context of 3D human reconstruction. Network intrusion detection systems are investigated using CNN, LSTM, and CNN + LSTM models; Evacuation training systems employ the rainbow-deep Q-network to simulate dynamic evacuation scenarios. Gesture recognition is addressed through multilayer perceptron and feedforward deep neural network models, enabling delicate skin-related gesture control. Another important aspect of AI in the Metaverse is the personalized content recommendation and user assistance. AI algorithms analyze user preferences, behaviours, and interactions within the virtual environment to provide tailored recommendations, guiding users towards relevant content and experiences. AI-powered virtual assistants can offer real-time support and guidance, enhancing user engagement and facilitating seamless navigation in the Metaverse. AI is also crucial in ensuring a safe and secure metaverse experience. AI-based systems can detect and prevent malicious activities such as fraud, hacking, or unauthorized content distribution. Additionally, the Table showcases the utilization of AI techniques in various domains, such as computational linguistics for recommendation systems, convolutional neural networks for finger vein recognition, and YOLO (You Only Look Once) for gesture recognition in education. Other areas of investigation include image classification, control and management using the MDP, digital content protection, natural language processing for prediction of user satisfaction, 3D point cloud classification in Metaverse applications, human image synthesis, singer identification through audio processing, and smart home technologies. All this can happen through different AI directions such as knowledge-based systems, computational linguistics, identification and authentication, emotion classification, image classification, control and management, digital content protection, natural language processing, 3D point cloud classification, human image synthesis, audio processing and music information retrieval, smart home technology, and more. AI methods enable the generation of lifelike and responsive virtual beings capable of interacting with users and simulating human-like behaviours. Through NLP and computer vision, these virtual characters can understand and respond to user commands, engage in meaningful conversations, and exhibit emotions, enhancing the sense of presence and social interaction in the Metaverse. Various AI techniques and models are employed across the studies, such as MTCNN, CNN, RNN, LSTM, YOLO, and GANs. In addition, RF, Naïve Bayes, KNN, LR, LightGBM, and Catboost. These methods highlight the utilization of both traditional and advanced machine learning and deep learning approaches. The "Metrics Used" criteria in the Table presented the evaluation metrics or measures used to assess the performance of the proposed methods. These metrics may include accuracy, precision, recall, F1 score, RMSE, and EER. The choice of metrics depends on the nature of the problem being addressed in each study. The "Application" column highlights the practical application or domain to which each research or project is targeted. This includes areas such as 3D human reconstruction, intrusion detection systems, evacuation training, gesture control, metaverse robots, recommendation systems, singer identification, digital content protection, prediction of user satisfaction, aircraft maintenance education, and more. The Table also indicates the presence or absence of specific technologies and approaches. AR, VR, IoT, NLP, computer vision, machine learning, GANs, reinforcement learning, virtual assistant technology, semantic web, multi-agent systems, NLG, predictive analytics, and computer graphics are among the technologies and approaches employed in the studies. Finally, the Table comprehensively overviews different AI research directions, methodologies, applications, and associated technologies. It showcases the diversity and breadth of AI research and highlights the areas in which different techniques and technologies are applied to solve various problems and challenges. Future AI in the Metaverse has a lot of potential, as we can see. The capabilities of virtual characters, environment generation, and user interactions will continue to be improved by developments in AI technologies like deep learning, reinforcement learning, and neuro-symbolic AI. Experiences in the Metaverse will become increasingly more immersive and connected as AI is combined with cutting-edge technologies like VR, AR, and the IoT.

6.5 Mixed reality & hologram

Mixed reality (MR) and holograms play crucial roles in the Metaverse, offering immersive and interactive experiences. MR combines the real and virtual worlds, enabling users to interact with virtual objects while maintaining awareness of their physical surroundings. Within the Metaverse, MR facilitates virtual collaboration, immersive commerce experiences, and augmented entertainment, breaking down distance barriers and enhancing user engagement. Holograms, projecting three-dimensional images into space, bring a sense of physical presence and depth to the Metaverse. They find applications in virtual conferencing, performances and events, education and training, and spatial computing, providing realistic interactions and enhancing user experiences. Overall, MR and holograms enrich the Metaverse by blurring the boundaries between reality and virtuality, creating dynamic and engaging environments for users to explore and interact with.

6.5.1 The integration of physical and digital worlds through mixed reality technology.

Mixed reality and the Metaverse are popular in technology and virtual experiences nowadays. Before assessing their association, each issue must be examined separately. Mixed reality combines VR and AR technology so that the physical and digital worlds may interact in real-time. A holistic setting is created by overlaying virtual components over the actual environment or integrating digital entities with their physical surroundings. Mixed reality experiences often involve headgear or gadgets to help people see and interact with virtual material (Liberatore and Wagner 2021 ). The Metaverse is a dynamic, all-encompassing virtual world that includes virtual reality, augmented reality, and the internet. The phenomenon is a lasting, all-encompassing, and linked domain of computer-generated environments where people may interact synchronously with other people and digital things. A shared, permanent, and diversified infrastructure that allows social interactions, business transactions, leisure pursuits, intellectual pursuits, and other undertakings is the Metaverse: mixed reality and the metaverse attempt to provide immersive, interactive digital experiences. Mixed reality may help you enter and explore the Metaverse. They integrate virtual and physical content to make metaverse interaction more fluid. The Metaverse provides a vast infrastructure for mixed-reality experiences. This is done by providing a platform for virtual content production and sharing, user connection, and social interactions (Siyaev and Jo 2021). The Metaverse may influence many areas of human existence. Technology might change social relations by allowing people from different regions to collaborate and communicate in virtual settings. Immersive experiences and interactive story frameworks may transform entertainment and gaming using virtual reality technology. Virtual learning environments, markets, and innovative business models in the Metaverse may alter education, commerce, and other industries. Companies and developers are working to create the Metaverse, which is still under development. Technology leaders and entrepreneurs invest in virtual reality, augmented reality, and related technologies to build a metaverse. Open standards, interoperability, and safe technologies are essential for a decentralized, inclusive metaverse that benefits all stakeholders. It is crucial to explore mixed reality and metaverse challenges and concerns. To create a sustainable and inclusive metaverse, privacy, security, ethical considerations, digital ownership, and the digital divide must be addressed to protect individual rights and promote positive experiences (Liu et al. 2023 ). Mixed reality and the Metaverse are interconnected and may change how we use digital media and communicate. The Metaverse provides a more extensive framework for collaborative, immersive, and interrelated virtual interactions. The prospective effects of these principles on human connection, communication, and digital experiences as technology and the metaverse advance are intriguing.

6.5.2 The integration of immersive realities through the utilization of holograms and the Metaverse.

Hologram optics and photonics research is extensive. Science and engineering researchers have investigated many methods to build high-quality holographic displays and enhance hologram recording and reconstruction. Academic research has focused on holographic materials, recording mediums, and display technologies (He et al. 2023 ). Metaverse research spans computer science, human–computer interaction, virtual reality, and social sciences. Scholars have studied immersive and interactive virtual worlds, genuine personalities and digital representations, and metaverse communication and interaction systems. The metaverse and holographic technologies provide new academic opportunities. Academic scholars may study the technological challenges of holographic displays in virtual reality. This involves improving real-time holographic rendering and developing new projection methods to improve immersive experiences. Scholars may also study how holographic portrayals affect metaverse user engagement, immersion, and communication. Analyzing user perceptions and experiences with holographic objects or avatars is one possibility. Researchers may also examine how holograms improve virtual communication and cooperation (Upadhyay and Khandelwal 2022 ). Academic institutions may build specialized research labs or institutes to study holography and the Metaverse, boosting cooperation between optics, computer graphics, and human factors experts. The collaborations might advance holographic technology and provide more immersive and genuine metaverse experiences. Furthermore, researchers might analyze the ethical and social effects of holographic technology and the Metaverse. One possibility is to study the impact of broad holographic representations in education, entertainment, and communication (Dwivedi et al. 2022 ). To conclude, holograms and the Metaverse are studied across many academic fields. Technology scholars are developing holographic technologies, creating and executing immersive virtual worlds, and studying their social and ethical effects. The authors’ study might lead to new holography and metaverse applications and experiences.

7 Future research implications of metaverse-AI convergence

The metaverse and AI convergence opens new virtual experiences and interactions. This symbiotic relationship’s potential advantages and drawbacks needs more examination.

Academics & Researchers: Researchers benefit from a comprehensive metaverse and AI research study. This attempt helps identify knowledge gaps, builds on previous work, and stimulates the exploration of unexplored territory in this subject.

Impact on Technology Companies and Developers: Systematic assessments can forecast metaverse-AI developments. These insights help technology organizations and developers enhance current technologies, uncover unexplored opportunities, and make educated product and investment choices.

Policymakers/Regulators: As the Metaverse and AI advance, policymakers and regulators must understand their potential impacts, possibilities, and difficulties. Evidence-based policies, regulatory frameworks, and ethical norms may be developed and used from a systematic review.

Implications for Entrepreneurs and Startups: A detailed assessment may aid entrepreneurs and startups entering the Metaverse and AI. This endeavour helps analyze the marketplace, find profitable possibilities, and provide insights to create new goods and services.

Investors and Venture Capitalists: Systematic assessments may help investors evaluate research progress, economic prospects, and technology improvements in the metaverse and AI initiatives. These analyses help investors choose potential enterprises.

Value to Educators and Students: Systematic reviews provide complete Metaverse and AI insights. These evaluations help educators build courses, direct student research, and improve knowledge of this diverse topic.

Healthcare and Medicine: The Metaverse and AI can alter healthcare and medicine. Virtual simulations and AI-powered medical models may transform medical education and patient care by delivering realistic training situations and individualized treatment plans based on patient data.

Implications for Agriculture and Environment Conservation: The Metaverse and AI provide great prospects for sustainable agriculture and environmental preservation. AI-powered metaverse apps improve resource use and reduce environmental effects.

A rigorous investigation of the metaverse-AI nexus finds many possible ramifications across many areas. This study emphasizes the significance of educated decision-making, ethical concerns, and extensive research to harness this strong integration’s revolutionary potential properly. The Metaverse and AI have promising futures, requiring ongoing research and multidisciplinary cooperation.

8 Conclusion

In conclusion, a notable research gap persists in exploring different aspects of the Metaverse and resolving prevailing issues and obstacles in this domain. The systematic analysis conducted in this study has underscored the necessity for additional investigation into AI methods to enhance trustworthiness. Furthermore, a more comprehensive assessment of the performance of deep learning and machine learning approaches is required to cultivate dependable and precise models. Enhancing comprehensive datasets, thorough scrutiny, and evaluations of proposed methodologies and applications also emerge as improvement areas. The immersive digital world of the Metaverse, driven by virtual reality, presents the potential for limitless encounters and is closely intertwined with the advancement of AI, sparking considerable academic intrigue. Prospective implications encompass Entrepreneurs and Startups, Investors and Venture Capitalists, Educators and Students, and Healthcare and Medicine, where AI-driven virtual simulations and medical models have the potential to revolutionize medical training and patient care through realistic scenarios and tailored treatment plans based on patient-specific data. Policymakers must prioritize funding for interdisciplinary research, establish regulatory frameworks for responsible AI deployment, and promote collaboration to address ethical considerations in the Metaverse. Moreover, a Metaverse enriched by AI introduces dynamic settings, intelligent avatars, and personalized experiences, enriching realism and engagement. However, this also introduces ethical deliberations, necessitating a harmonious balance between innovation and the responsible utilization of technology to ensure a constructive and secure digital cosmos. Sustained exploration and progress in AI methodologies, data accessibility, and evaluation approaches are imperative to tackle the gaps and challenges in the Metaverse arena and augment our capacity to mitigate their consequences effectively.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Artificial intelligence

Science direct

IEEE Xplore

Web of science

Intelligent non-player characters

Human–computer Interaction

Internet of things

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Convolutional neural networks

Augmented reality

Arabic sign language

Virtual reality

Deep learning-based asymmetric virtual environment

Adaptive accelerated learning

Circular waveguide to coaxial transformer

Deep autoencoder

Generative adversarial network

Medical technology and AI

Proton-exchange membrane fuel cells

Deep neural network

Electromyogram

Facial expression recognition

Maximum mean discrepancy

Contrastive adaptation network

Convolutional recurrent neural network

Valence aware dictionary and sentiment reasoner

Light gradient-boosting machine

Term frequency–inverse document frequency

Triboelectric nanogenerator

Borderline personality disorder

Extended reality

Digital twin

Deep reinforcement learning

3D morphable model

Mixed reality

Gated recurrent unit

Recurrent neural network

Long short-term memory

Human–machine interfaces

All-in-one multifunctional

Three dimensional

Federal trade commission

2D visual attention

User interface

Explainable AI

Electroencephalogram

General data protection regulation

Multi-criteria decision making

Fuzzy Weighted with zero Inconsistency

Fuzzy decision-by-opinion score method

Natural language processing

Natural language generation

Multi-task cascaded convolutional networks

You only look once

Markov decision process

Random forest

K-nearest neighbor

Logistic regression

Root mean square error

Equal error rate

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Contributions

Mohammed A. Fadhel: Methodology, Writing—Original Draft, Writing—Review & Editing, Visualization Ali M. Duhaim: Methodology, Writing—Original Draft, Writing—Review & Editing, Visualization A. S. Albahri: Supervision, Methodology, Writing—Original Draft, Writing—Review & Editing, Visualization Z.T.Al-Qaysi: Conceptualization, Methodology, Software, Validation, Formal analysis, Review & Editing, Visualization M. A. Chyad: Software, Validation, Formal analysis, Review & Editing, Visualization Wael Abd-Alaziz: Software, Formal analysis, Review & Editing Laith Alzubaidi: Conceptualization, Methodology, Supervision, Validation, Writing -Original Draft, Writing—Review & Editing, Formal analysis, Funding O.S. Albahri: Supervision, Validation, Formal analysis, Investigation, Writing -Original Draft, Writing—Review and editing, Visualization A.H. Alamoodi: Supervision, Data Curation, Validation, Writing—Review & Editing Ashish Gupta: Software, Formal analysis, Review & Editing, Visualization, Funding Yuantong Gu: Supervision, Validation, Writing -Original Draft, Writing—Review & Editing, Funding All authors reviewed the manuscript.

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Fadhel, M.A., Duhaim, A.M., Albahri, A.S. et al. Navigating the metaverse: unraveling the impact of artificial intelligence—a comprehensive review and gap analysis. Artif Intell Rev 57 , 264 (2024). https://doi.org/10.1007/s10462-024-10881-5

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