Gaining traction in the late 1980s and early 1990s, eLearning emerged initially through interactive video LaserDiscs and later via CD-ROMs, as personal computers became common in the workplace. By 1991, the web was making waves, yet few saw it as a learning platform due to limited multimedia capabilities. But in 1996, Macromedia Flash changed everything, opening doors to interactive online experiences. Flash quickly became a go-to, primarily across entertainment, gaming and education, making it possible to create interactive multimedia experiences that could be distributed on the internet.

The digitalization of corporate learning brought with it learning management systems (LMSs), which allowed companies to structure and manage eLearning. This shift also introduced authoring tools for quickly building and distributing basic, text-and-image courses. Through the early 2000s, immersive productions coexisted alongside simpler “click-next” courses, with Shareable Content Object Reference Model (SCORM) launching in 2000 to standardize content delivery across platforms.

Then came social media in 2006, changing online interactions and further influencing corporate learning. Intranets soon blended communication, learning, and culture-building. With the 2007 release of the iPhone, mobile devices joined the eLearning landscape. Yet, as digital courses took off, they largely became associated with simple, static content: text, images and quizzes.

In 2012, virtual reality (VR) headsets like Oculus Rift ushered in a new wave of immersive projects, bringing higher engagement but facing high costs and logistical barriers. While VR seemed poised to redefine training, its corporate adoption remained limited. By 2021, even as the Metaverse promised revolution, adoption stagnated. Perhaps artificial intelligence (AI), which emerged in the meantime, is the game-changer we’ve been waiting for… and nothing will ever be the same again. Or will it?

Is history repeating itself? Will technology continue driving corporate learning?

What if the biggest driver of digital corporate learning has always been technological development rather than pedagogy? Early digital courses emerged because companies needed to train large workforces more affordably.

Training went digital, often leading to quick, template-based “click-next” courses. Instructional designers were tasked with working within these tools rather than having the freedom to create truly engaging experiences. This reliance on technology for efficiency resulted in a divide: low-cost eLearning, which was easy to scale but less engaging, versus high-cost, immersive content that proved difficult and expensive to produce.

External production companies were typically needed, and the lack of in-house expertise created further obstacles. While research continues to show the advantages of immersive learning, such as improved engagement and skill retention, companies have mostly maintained traditional training formats.

Reports from PwC and Deloitte provide clear evidence: VR-trained employees learn four times faster than in classrooms, experience a 275% boost in confidence applying skills, and feel a 3.75 times stronger emotional connection to content. VR and AR have also been shown to improve soft skills, including communication and conflict resolution. Yet, many companies remain hesitant to adopt these approaches, often defaulting to familiar “slide-and-quiz” formats. A McKinsey report featured by Training Industry highlights how simulations help close the gap between theoretical knowledge and real-world application, an effect we know is achievable, but which many companies still forgo due to cost and time barriers. Could AI be the catalyst to shift this trend?

The learning designer’s dilemma: efficiency vs. engagement

Historically, learning designers have been constrained by efficiency-driven tools and budget pressures. Creating immersive learning experiences, while effective, was time-consuming and required multimedia skills that went beyond most designers’ expertise. Many instructional designers became “jacks of all trades,” dabbling in animation, scripting and programming to elevate their courses. Yet, their core expertise remained in pedagogy, not graphic design or multimedia production.

AI offers a unique solution to this dilemma, allowing instructional designers to accomplish more independently and with high quality. In a recent interview, Dr. Robin Sargent, founder of IDOL Academy, compares today’s instructional designers to “Swiss Army knives,” blending technical and creative skills to deliver impactful learning. “They can do it all,” she notes, emphasizing how designers must now skillfully integrate pedagogy with technology.

How AI Is Transforming Corporate Training

Many learning and development (L&D) professionals still view AI primarily as a tool for faster content creation.

According to the report “AI in L&D: Intention and Reality,” while AI accelerates production, its potential for enhancing content quality often goes overlooked. The report raises an essential question:

“Are respondents so focused on creating content quickly that they overlook AI’s potential to improve quality? Or do practitioners believe that AI cannot improve the quality of content? If so, is this because they feel their content is already of high quality due to the role of practitioners, or do they consider AI incapable of producing good quality content, or perhaps they don’t know how to use AI for this? Finally, this result poses an uncomfortable question: Is quality simply not the top priority for L&D practitioners?”

This insight underscores the transformative shift AI could bring, not only for faster content creation but for unlocking new ways of learning that prioritize quality and engagement. However, realizing this potential requires instructional designers to skillfully leverage AI tools, creating immersive, scenario-based content, interactive simulations and adaptive feedback systems.

This shift allows them to develop engaging learning experiences that blend theory with real-world application, free from the high costs and long timelines once associated with immersive learning.

By empowering instructional designers to focus on pedagogy over technical or financial limitations, AI effectively brings control back to the pedagogue. As a result, immersive learning is now more accessible than ever, enabling designers to explore its full potential.

The essence of immersive learning and its key benefits:

Immersive learning is about creating engaging, hands-on experiences that simulate real-world environments. By leveraging technologies like virtual and augmented reality, simulations, and interactive storytelling, learners can develop skills in a safe, controlled setting that mirrors actual job scenarios.

For corporate training, immersive learning offers unique benefits:

 1. Real-life scenarios

 Immersive training places learners in lifelike situations, making retaining knowledge and applying skills easier

 2. Interactivity 

Learners actively participate, making choices and navigating scenarios that reflect workplace challenges.

 3. Sensory immersion

Multimedia and sensory elements enhance realism, boosting engagement.

 4. Timely feedback

Real-time guidance and feedback help learners track progress and understand their decisions.

 5. Clear objectives

Structured goals provide direction, ensuring learners understand their purpose and learning outcomes.

These principles not only elevate engagement but also enhance knowledge retention. As Christy Tucker, recognized instructional designer and founder of Syniad Learning, points out, effective immersive learning can also be designed through simpler “mini-scenarios” that make assessments relevant without overcomplicating production.

Tips for implementing AI-powered immersive learning:

Creating impactful immersive experiences with AI may seem daunting, but a few practical strategies can make it more approachable. Here are 4 tips from Stine S. Snekkenes, senior instructional designer at We Are Learning:

  1. Begin by developing mini-scenarios that target key skills.

Mini-scenarios are less complex to design but offer depth, allowing learners to make realistic decisions without a full-scale simulation.

  2. Use AI tools for content generation.

This could range from adaptive branching to custom feedback. AI-driven tools like scenario generation and virtual facilitators can enhance engagement without extensive programming.

  3. Prioritize engagement (with sensory and interactive elements).

Incorporate multimedia, audio cues and gamification to draw learners into the experience.

  4. Gather feedback for continuous improvement.

Collect insights from learners on how immersive elements impact their understanding and application, and edit scenarios accordingly.

The Future of Immersive Learning With AI

The impact of AI goes beyond making learning faster and cheaper; it has the potential to redefine what e-learning can achieve. Freed from technological and budget constraints, instructional designers can now craft engaging, transformative experiences that put learners at the center. As Forbes projects, behavioral skills, which human resources (HR) expert calls “power skills,” will drive the future of work, and immersive learning will be essential in developing these competencies.

Moving forward, it’s up to instructional designers and all learning leaders to creatively leverage AI, opening doors to a new era in corporate learning. The vision is to place learners at the heart of engaging, impactful training. With AI-powered immersive learning, the future is looking bright.