The conversation around AI in learning and development has evolved fast, from cautious experimentation to a race for real impact. In this episode of the L&D Podcast, I spoke with L&D advisor and researcher Egle Vinauskaite to unpack why this is such a pivotal moment for L&D.
Egle is co-author of The Race for Impact report, a survey of 600 global L&D professionals on the innovative ways AI is being put to use today. For the first time, over half of L&D teams report actively using AI, rather than just experimenting with it. That shift brings both opportunity and urgency.
AI has made content easier and cheaper to produce. But this very fact challenges L&D’s traditional value proposition. Together, we discussed why the center “cannot hold,” the barriers holding teams back, and the new operating models she calls the Transformation Triangle.
If you want to move beyond AI hype and into meaningful implementation, this conversation provides clarity, challenges, and a roadmap for what comes next.
Listen to the full episode below. Find more conversations about the future of Learning and Development here.
1. L&D is at a turning point
For Egle, L&D is at a seminal point. The profession must choose how to evolve, or risk becoming obsolete.
“For the first time in three years, over half of the people who responded to our survey indicated they’re using AI rather than experimenting or piloting. So AI gives L&D the tools to generate greater impact, but it has also increased the risk of doing nothing.”
As AI makes it effortless for anyone to create learning content, Egle argues that we can no longer define our value through production alone.
“AI has made the value of content plummet. It has removed the barriers to anyone becoming a content producer. What is the purpose and value add of L&D when people can get what they need themselves?”
Content creation alone is no longer enough. This shift demands a fundamental rethink of purpose and strategy.
2. From experimentation to implementation
Egle’s research shows that AI in L&D has moved quickly from theory to practice. Teams have gone from small pilots to real implementation at scale.
“AI use keeps increasing. We’re seeing more sophisticated use cases beyond content creation: AI for analytics, for skill development, for strategy and research.”
Egle noted a tenfold increase in teams using AI for data analysis and to measure impact.
“This might seem like a small win, but it gives L&D the ability to target efforts, monitor impact, and improve over time. That’s been difficult for us historically.”
The message is clear: L&D teams that treat AI as a strategic partner, not a gimmick, are already delivering deeper value.
3. The barriers, and how to move past them
Despite clear growth in AI usage, progress hasn’t been uniform. Many teams still struggle with data privacy, security concerns, and a lack of AI skills. But Egle believes these are solvable problems, if addressed deliberately.
“On the skill side, we know the formula: give people role-based training, clear guidance on what they can and can’t do, and real use cases to start with. Then create opportunities and incentives to play.”
She also distinguishes between real and perceived data privacy risks. “AI vendors are competing on enterprise-grade security. But smaller companies using what I call ‘retail AI’ do need to be more cautious about what they feed into these tools.”
Ultimately, the real risk is not trying at all. “Awareness and utilization of AI are becoming table stakes for L&D. Even if your current job doesn’t use AI, your next one probably will.”
“We know the formula: give people role-based training, clear guidance on what they can and can’t do, and real use cases to start with. Then create opportunities and incentives to play.”
4. The transformation triangle: three paths forward
To help teams navigate what comes next, Egle and her co-authors developed the Transformation Triangle: a model outlining three potential futures for L&D.
“In the report we’re saying that L&D can’t stay a content producer or it’ll disappear. So what are the options?” The Triangle proposes three potential outcomes:
L&D as a skills authority
“In this future, L&D stays relevant by making skills a core business currency and applying deep learning expertise to build them at scale.”
This model requires L&D to professionalize deeply in learning science, behavioral design, and analytics.
L&D as an enablement partner
“Here, L&D embraces decentralization and shifts from owning learning to empowering experts in the business.”
It’s a model built on trust and collaboration. Learning and development professionals help organizations capture, share, and create knowledge.
L&D as an adaptation engine
“In this future, L&D is no longer a standalone function. It’s absorbed into blended teams that build adaptability across the organization.”
Here, the function to build vital skills is built into existing teams, rather than sitting alongside them.
Each model represents a different response to the same challenge: redefining value in an AI-powered workplace.
5. Redefining value through enablement and expertise
Egle offers a few case studies from the report to show what the future could look like:
“An international consulting firm gave employees access to secure, in-house AI tools. Once they could build their own performance support bots, the L&D team realized employees could create better tools than we ever could.”
L&D’s role shifted from producer to orchestrator: spotting interesting innovations, setting guardrails, and helping scale up the parts that really work.
In another case, a global outsourcing company used AI to build skills frameworks and personalize coaching at speed. Their “secret sauce,” Egle explained, was the learning science and intent behind this work.
“The tools are already available. What makes the difference is the intent—knowing what you need to achieve—and the unique expertise you infuse those tools with.”
Both examples point to the same future: L&D creating ecosystems for performance, not just programs for learning. Egle’s research and insights highlight the fact that L&D can’t simply stay where it is. AI has changed the rules, and the function’s relevance will depend on how boldly it redefines its role.
Whether we become skills authorities, enablement partners, or adaptation engines, our value will come from helping the business and workforce adapt faster and smarter than ever before.
“The key lesson is not to cling on, but to recognize the change happening, identify where the value lies, and adapt accordingly.”
About Egle Vinauskaite
Egle Vinauskaite is an advisor and researcher who helps L&D teams integrate AI into their operations and prepare workforces with the skills needed for effective adoption. She has a sharp view of how AI is redefining the role of L&D and creating new possibilities for learning in the workplace.
Egle brings extensive expertise in learning, behaviour, and technology, working with both global enterprises and emerging edtech innovators. Her background spans AI, XR, mobile learning, digital platforms, and blended learning design, giving her a unique perspective on how technology is reshaping organisational learning and the future of work.
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