Generative AI Will Bring the Metaverse to Fruition

Although artificial intelligence (AI) has existed for decades, it is now at the forefront of information technology due to its level of maturity, increasingly widespread adoption, and possible revolutionary impact on insights and productivity. The surge of interest in AI also is due in no small part to the introduction of generative AI products such as ChatGPT and Dall-E by OpenAI, which are among the first to provide an intuitive, common, direct, and easy interface through voice and keyboard so that almost anyone can experience, experiment and work with AI.

While AI is receiving so much attention and is here to stay, another potentially important development in information technology, the metaverse — the immersive internet of virtual and augmented reality — received similar attention in 2021, but its adoption and awareness dropped steeply and now has been eclipsed by the conversation around generative AI.

Why the Metaverse Lags Behind AI.

The metaverse is behind AI in mindshare and adoption for four reasons:

• The metaverse is a place or at the very least a medium. Generative AI is a means to an end or ends.
• Despite this important distinction, the ease of use that chat GPT has brought to the interface to connect with their generative AI cannot be understated. Nearly everyone is used to typing (or using speech-to-text, etc.) into a chat box. The interface of virtual and augmented reality headsets creates friction because it requires considerable change for us to use the headsets, interact with a medium, and indeed inhabit a different realm than what we’re used to.
• The language components of the metaverse and its visual components such as avatars are not sufficiently lifelike to inspire mass adoption, especially in retail environments that need to closely resemble in-person experiences to succeed.
• After three years in relative isolation during the pandemic, there is a strong desire to return to real life rather than inhabit a virtual world in addition to many online meetings.
• It’s much more difficult to create a compelling, convincing, immersive virtual experience that approximates real life than it is to apply AI algorithms to various discrete tasks such as copywriting, analytics, and decision support.

Economics and practical applications also are important factors in the widespread adoption of AI.

Recommended: How to Get Started with Prompt Engineering in Generative AI Projects

With AI, deeper and more accurate insights from improved analytics can lead to better decisions which usually provide economic and productivity benefits and ROI. With the metaverse, immersive experiences such as reviewing a virtual product design or shopping in a virtual store with virtual clothing try-ons are mostly further out in the future and nowhere near rivaling or replacing current e-commerce and in-person retail experiences and revenue.

Generative AI Can Unlock The Metaverse.

The lagging metaverse now has a newfound enabling technology in generative AI to achieve its potential for widespread adoption, lifelike immersive experiences, and the scalability required to deliver such experiences across languages, cultures, and markets. Now that we can create any imaginable image just by speaking or typing it and automated language translation services are increasingly maturing and common, the metaverse has the potential to come to fruition to a point where the equipment and behavioral change required will be worth it to receive its benefits. It’s important to note that image generation via AI still is too low quality and not true-to-life enough to enable visual experiences in the metaverse to be suitable for mass adoption. That will change with time, and when it does, there will be a dramatic uptick in metaverse adoption as the visuals in those virtual spaces will become indistinguishable from real-world spaces (e.g., you will look like you, not an avatar).

Possible future benefits of the metaverse in a retail environment include generating and interacting with lifelike virtual versions of the human customers and salespeople as though they were in-person and in the culture and language of the customer. All of the complexities and nuances of in-person communication will be a major challenge to emulate virtually, but generative AI increasingly will be capable of closely approximating so many subtleties.

Rather than the current avatars that are fuzzy approximations of a person or downright “bizarro” versions of a person, future avatars will look exactly like that person and will enable virtual try-on of clothing, jewelry, hairstyle, makeup, and accessories that look exactly like their real-world analogies. That should lead to the final promise of higher rates of customer satisfaction and conversion and lower return rates.

Look Before You Leap with Generative AI Metaverse

However, a note of caution: The lifelike metaverse and its potential for widespread adoption are closer than ever but still in infancy.

Therefore, proceed slowly and invest prudently, and, most importantly, understand the problem or goals first before examining and adopting potential solutions.

Although generative AI has countless use cases for customer service, customer experience, and metaverse applications, carefully evaluate the possibilities and decide whether any use cases are right for your business now. While some organizations may have a problem that can be solved or a goal that can be achieved through generative AI or other AI or metaverse applications, it may not be the right timing for your business. Many of us remember or know about the e-commerce meltdown at the turn of this century when many e-commerce startups went out of business due to a lack of sufficient revenue; let’s not repeat it by overinvesting in new technologies without the fundamentals to support them.

The pressure on startups from investors sometimes is immense to dedicate resources to the current or next big thing, while established companies sometimes are perceived to lack innovation compared to disruptive startups.

Both innovative startups and more cautious established organizations need to apply the same thinking: Define problems and goals, and then determine the best methods and technologies to address them within appropriate and allocated budgets.