L&D Podcast Live: How AI Can Boost Skills & Performance

AI hype and confusion is all over L&D today. Amid bold predictions and big promises, many teams are still trying to work out what AI actually means for their day-to-day work.

But where does AI genuinely add value, and where is it simply helping us do the wrong things, faster?

In a live edition of the Learning & Development Podcast, I was joined by Egle Vinauskaite, Ross Stevenson, and Peter Manniche Riber to talk all things AI. We explored how AI is being used in L&D today, which tools and use cases are starting to make a difference, and how AI can support performance, capability, and skills development.

We also looked at where L&D teams are getting stuck, from security and capability constraints, to cautious organizational mindsets, and where the biggest opportunities are. Finally, we discussed what AI could help L&D evolve, and how its value could be perceived across the business.

Below are just five of the many fascinating insights from the discussion. Listen to the episode for much, much more.

1. AI has moved from experimentation to real-world use

The L&D profession has reached a critical milestone in AI adoption. In a recent report, Egle’s substantial research found that “for the first time, the majority of our respondents reported using AI instead of just experimenting with it or piloting it. We’ve passed 50% for the first time."

For now, AI use is largely focused on efficiency gains in areas like content creation, administration, and learning design support. While valuable, these uses keep L&D in its traditional place, rather than unlocking AI’s full potential to change how learning supports the business.

But more use cases are taking root. “Content is still the main use case,” says Egle. But “some also use AI for skill development. Conversational bots where AI helps you develop skills, coaches you, and so on.

“And then using AI for strategy. Things like creating skills frameworks, and AI being a sparring partner in learning strategy creation.”

The panellists agreed that simply using AI to produce more stuff isn’t going to bring meaningful results. But it can unlock critical business wins if L&D teams reimagine their purpose within the organization.

2. L&D must shift from content delivery to problem-solving

AI makes it easy to produce more content, but that doesn’t necessarily improve performance or capability. The panelists agreed that while AI makes content creation faster, L&D's true value comes from putting this efficiency to better use.

"We're not here to create content,” says Peter. “We’re here to solve business problems, to help the business, and to help people learn.”

Egle says that AI “allows us to ditch a lot of static content and replace it with practice that helps people build real skills. Because we know that content does not equal skills for people.” L&D leaders must therefore use AI to enable practice, feedback, coaching, sensemaking, and skills development.

“We definitely don’t solve business problems by creating more content or creating it faster.”

— Peter Manniche Riber

Smarter AI use helps people perform better in real work situations, rather than consuming more learning materials. Provided you focus on the right applications.

3. The real opportunity lies in transformation

Tangibly, how should L&D teams involve AI in their work? Egle’s research and consulting work found five core uses:

Content: Faster and more efficient course creation
Practice: Simulations, coaching, and dynamic feedback
Memory: Turning conversations and documents into usable organizational memory
Context: AI helps employees in the flow of work, not as an external or parallel service
Intelligence: AI lets L&D teams manage skills as a strategic business resource

“L&D is mostly using the two that keep [the profession] in the same role: content and practice. They’re in what I call the evolution zone. But the real opportunity lies in the three that redefine L&D's value proposition and ways of working: memory, context, and intelligence. This is the transformation zone."

While AI can enhance content and practice, its transformative power comes from storing and surfacing institutional knowledge, supporting people in their work, and managing skills as a strategic business resource.

Instead of focusing on new courses to create, AI lets L&D teams deploy learning in more hands-on, practical interactions throughout the flow of work.

4. L&D teams must rebuild from the foundations

So what’s holding teams back? Many organizations are applying AI to old, outdated learning models. And according to Ross, we may be rushing it:

“The pace is so fast that it feels like people don't really have the time or space to sit back and say, what would this look like if it was different?”

"Too many are just bolting AI onto an existing model, rather than stepping back and saying, does that model still serve us today? And how do we transform that model for the modern era and the technology that we have?"

— Ross Stephenson

In many cases, what’s required is a new architecture or approach to take full advantage of AI.

"We need to rethink the processes and how we help people,” says Peter. “What data foundation do we need so that artificial intelligence can actually make a difference?"

Again, this comes back to moving away from content creation and towards solving real business problems. L&D teams must identify true business problems or objectives first, and then use AI to enhance and transform their approach.

5. Meaningful impact requires a targeted approach

The massive range of possibilities AI offers are both a gift and a curse. With so many potential use cases, it’s hard to know where to begin.

The key to successful AI implementation is clarity of purpose. Technology alone cannot solve problems that are not first clearly defined. “Where can it make a difference, and is it worth the investment?” asks Peter. “Because it's not cheap to do and to run.”

“No tool alone is going to create long-term meaningful change in an organization. You need a combination of technology, the people in your organization, and the systems that live in that organization—both digital and physical systems.”

— Ross Stevenson

Once again, teams that reposition around solving business problems and improving performance have the best chance of success. “You have to think like a business in order to solve your business problems,” says Peter.

Employ AI as a key tool to tackle precise, well-defined challenges. Keep a narrow focus, with clear business objectives in mind, and avoid simply delivering more, faster, but with no greater purpose.

AI can be a transformative tool for our L&D teams, provided we’re willing to transform along with it.

About the experts

Egle Vinauskaite is a learning, behavior, and technology specialist who works with global enterprises and emerging edtech innovators. As both advisor and researcher, she helps L&D teams integrate AI into their operations and equip workforces with the skills needed for effective adoption.

Ross Stevenson is a leading voice in the global L&D community, known for his practical, no-nonsense approach to modern learning. Ross brings a strategic yet pragmatic perspective on how L&D teams can evolve and remain relevant in an age of rapid technological change.

Peter Manniche Riber is an experienced L&D leader who until recently served as Head of New Tech, Digital Learning Solutions at Novo Nordisk, transforming HR and learning for a global workforce of 70,000+. Passionate about using technology to simplify and enhance learning, he experiments with generative AI, machine learning, adaptive platforms, and data-driven methods to deliver timely, effective solutions.