As generative AI reshapes how people work, learn, and perform, L&D teams are facing important questions about their role and value. In this interview, Egle Vinauskaite, Strategic Advisor, AI in L&D, at Nodes, discusses the people side of AI transformation, the changing value of content, and the commercial thinking learning professionals need to develop. She also offers a preview of the session she will lead at DevLearn, based on new research into how L&D professionals are using AI.
Q: What does your current role look like?
A: I advise organizations on the people side of AI transformation, and I’m particularly interested in how AI changes work and what that means for the conditions needed to support people’s development. Of course, I’m also interested in what shape L&D needs to take to play a part in that and add value in this context.
Q: What’s your favorite part of the work you do?
A: I get to solve very complex problems and that’s what keeps it, keeps it interesting for me. There is this inherent complexity, I would say, in anything related to people’s behavior, learning, performance—all of these things. And that complexity increases once you go up a level and you look at people’s systems and how they interact with the infrastructure, with the environment that people work in. And that obviously raises a lot of good problems to solve.
If we look at the bigger picture, AI transformation, both in L&D and in the broader business that that L&D supports, is obviously a very uncertain time. But it’s also a shock to the system that raises people-related questions that we haven’t considered before really, which I find endlessly fascinating to explore on a good day, of course.
Q: Is there a moment where your own thinking about AI completely changed?
A: I would say the moment that I tried generative AI for the first time, it was clear to me that it was a massive deal for L&D. Not just L&D’s work, but its role in organizations and the skills that L&D professionals need to stay relevant.
It also raised questions about the capability of L&D as a function, because the value of content plummeted, and with it, the value of L&D teams whose primary purpose and value proposition is creating content. I’m not saying that’s all L&D. I’m talking about L&D teams that define themselves in that way. In some cases, that value depletion was instant; in others, value started eroding slowly. So that’s one thing that was quite clear from the beginning. But at the same time, generative AI has presented L&D with the ability to create the kinds of upskilling and orchestrate expertise sharing in ways that we never could before. So that value claim is still there for the taking. And of course, this transformation has meant that the way businesses operate and how fast they need to change to react to competitive pressures, that has made the case for people development very salient. I’ll concede and I’ll admit that I did have a bit of an existential crisis back in early 2023.
Q: Which AI conversation do you think we’re spending too much time on? And which one are we not spending enough time discussing?
A: What L&D needs to become to keep adding value in this new business context where employees can use AI themselves, where they can build their own performance support tools, and where tools outside of L&D’s remit are also integrating AI to help people get their jobs done. I think that’s a massive question.
Q: Can you give us a sneak peek into the session you’ll be leading at DevLearn?
A: A bit of context here is that together with Donald Taylor, for the past three years, we have been running a global survey of L&D professionals asking how they are using AI in their work. And this year’s report comes out shortly before DevLearn, and that’s what I will be discussing and overviewing in my session. Where are the industries at how AI adoption in L&D has evolved over the past year? What’s real, what’s hype, and what the paths forward might be?
Q:What’s one skill every learning professional should develop over the next year?
A: I would say it’s commercial thinking: being able to look outside of L&D to understand how different parts of the business are changing with AI and what that means for the highest-value work L&D can do to support these changes, whatever shape the business and its separate functions are taking. I think ultimately that L&D leaders need to be not just learning leaders, but they also need to be business leaders.
