Before the artificial intelligence (AI) revolution, extended reality (XR)—a range of immersive technologies that blend the physical and virtual worlds—already was making significant strides as organizations began recognizing its potential for hard and soft skills training and teambuilding events.
As AI began to dominate the tech landscape, interest in XR momentarily waned as we sought to understand AI’s implications for learning. XR since has stabilized and proven its effectiveness, carving out its own special niche for learning and development (L&D).
Today, the fusion of recent AI applications for XR is generating renewed excitement, promising to make learning experiences more immersive, personalized, and responsive to learner needs.
4 AI-POWERED XR INNOVATIONS FOR L&D
1. AI-enriched XR role-playing experiences. AI has significantly influenced XR, particularly in creating more engaging and realistic virtual environments. One notable development is the introduction of AI-driven virtual characters or non-playable characters (NPCs) in gaming and online learning scenarios. Traditionally, NPCs operated on fixed scripts and limited, deterministic interactions. With AI, XR characters now can embody complex roles, emotions, and scenarios, making interactions in virtual training environments much more fluid and dynamic.
This development will be particularly impactful for role-playing situations, which most people find unsettling to participate in with coworkers. But with a more dynamic AI-enhanced XR environment, a learner could role-play with a character pretending to be an employee in a difficult situation and have it feel realistic. The AI-powered NPC can provide emotive and lifelike responses based on pre-defined guidelines, making the experience more educational and less awkward. In the future, these interactions will feel even more human.
It’s possible that AI will allow us to influence or adjust the conditions of a virtual learning experience by upping the ante in a safety scenario, adjusting world conditions, or perhaps creating a learning experience in real time, explicitly targeting a skill the AI detects the learner may feel less confident in.
2. Increasing realism in XR. When done well, putting on an XR headset can be a completely immersive experience. This level of immersion allows people to concentrate intensely on the situation at hand, provides a realistic yet safe practice environment, and connects people to one another more thoroughly than through a video meeting.
While hyper-realistic image renderings are desirable, L&D’s primary focus used to be on creating compelling and immersive learning experiences that didn’t necessarily require stellar visuals. Now, with higher rendering capabilities and a lower cost per learner, we can provide more detailed and realistic training scenarios.
The more real an XR environment feels, the more engaged learners will be. This is particularly true for practicing hard skills such as safety training, as an XR program can place learners in high-stakes situations with little to no risk involved. Tyson Foods, for example, saw a 20-plus percent reduction in injuries and illnesses after implementing virtual reality (VR) safety training.
3. Personalized XR experiences. AI also plays a critical role in personalizing XR experiences. Large Language Models (LLMs) can remember user interactions and adapt scenarios based on previous sessions. AI also is developing the ability to recognize context and nuance to a degree we originally expected but that it initially failed to provide.
This ability to recognize context and nuance has helped AI discern intent. When this is combined with XR technologies, the learning experience becomes deeply personalized, making it more relevant and effective.
In a recent podcast episode with Microsoft exploring the future of AI and learning, Sal Kahn, founder and CEO of Kahn Academy, said that AI will allow us “to increasingly approximate [the] type of one-on-one personalized experience that the best educations have always [had] throughout history, but to do it at scale.”
Additionally, on the backend, enterprise systems are becoming more sophisticated, allowing for secure access, tracking, and recording of XR interactions. This data-driven approach helps learners demonstrate their improvement and proficiency and learning organizations to prove the efficacy of learning.
4. Enhanced social learning interactions. AI can enhance social learning in XR spaces by addressing the issues of loneliness and lack of direction. Without strict time coordination, users may find themselves in sparsely populated or aimless environments. AI-driven NPCs can act as facilitators, guiding participants, fostering connections, and providing structure in these virtual spaces.
Over time, AI will enable more human-like interactions in virtual environments and could dynamically adjust scenarios to meet learners’ needs and provide just-intime performance support.
THE FUTURE OF XR IN L&D
The integration of AI with XR will continue to transform learning experiences. Innovations in XR hardware will further blur the lines between the virtual and real worlds, offering new possibilities for augmented and mixed reality learning experiences.
As tools and devices evolve, XR likely will become an indispensable part of every learning ecosystem.