Most conversations about AI in L&D fall into two camps: breathless enthusiasm (“AI will replace everything!”) or skeptical dismissal (“It’s just a fad”). Both miss the mark. The useful question isn’t whether AI matters for learning and development. It’s which parts of your work AI can actually improve and which parts it can’t touch.
Dr. Steve Hunt has spent decades at the intersection of technology and talent. He’s the author of a trilogy on HR tech, including Talent Tectonics, and previously helped build the talent function at SuccessFactors. When he talks about AI in L&D, he’s drawing on both deep technical understanding and practical experience watching organizations adopt (and misadopt) technology.
In a recent conversation with Ashish on the Risely podcast, Steve laid out a framework for thinking about AI that cuts through the hype. The core insight: AI is a powerful pattern-matching tool that automates repetitive work, but it doesn’t have wisdom, care, or the ability to make value-based decisions.
Watch the full conversation
Meet Dr. Steve Hunt
Dr. Steve Hunt is the Founder at i3 Talent LLC and author of the HR tech trilogy including Talent Tectonics. His career spans decades of building talent functions and studying how technology changes how people work. He brings a rare combination of technical depth and human-centered thinking to the AI conversation.
Connect with Steve: LinkedIn
What AI actually is (and isn’t)
Steve offers a mental model that’s useful for every L&D leader: think of generative AI as “an infinitely knowledgeable intern who’s eager to provide information but doesn’t know whether the information is correct.”
That framing changes how you use it. You wouldn’t hand an intern your entire leadership development strategy and walk away. But you’d absolutely ask them to research a topic, draft a summary, or pull together examples. Then you’d review their work, apply your judgment, and direct next steps.
AI is essentially a sophisticated pattern recognition system. It can interpret data, spot patterns, and make predictions. What it can’t do is care about people, make ethical judgments, or decide whether a decision is right in a human sense. It can help with decision-making, but it can’t ensure the decisions are correct.
Where AI is already changing L&D
Steve identified six areas where AI is making a practical difference for learning and development teams today:
Identifying skills people need to learn. AI can analyze job roles, performance data, and industry trends to surface skill gaps that would take human analysts weeks to identify. This moves L&D from reactive (“we need a course on X”) to proactive (“these 200 employees will need X within the next 12 months”).
Matching people to the right training resources. Instead of every employee browsing the same course catalog, AI recommends specific resources based on their role, skill gaps, and learning preferences. This is where the Netflix analogy actually works.
Delivering micro-learning in the flow of work. Short, contextual learning moments delivered at the right time. Rather than pulling people out of work for a workshop, AI sends relevant learning nudges that fit between meetings. Read more about AI in learning and development.
Democratizing coaching. Executive coaching used to be reserved for senior leaders. AI coaching makes personalized guidance available to everyone, from new managers to individual contributors. The coaching isn’t the same as working with a human coach, but it covers ground that was previously inaccessible to most employees.
Capturing knowledge from subject matter experts. AI can help extract and structure the tacit knowledge that lives in experienced employees’ heads. This is particularly valuable when those employees retire or move on.
Enabling immersive virtual learning experiences. From scenario simulations to virtual role-plays, AI makes experiential learning scalable in ways that weren’t practical before.
Where AI falls short
Steve is equally clear about the limits. Three limitations matter most for L&D:
AI doesn’t have wisdom. It can process every leadership book ever written, but it can’t tell you which advice applies to your specific organizational context. It doesn’t understand your company’s political dynamics, the unspoken norms on your team, or the personal history between two people in conflict.
AI blindly applies data. If the training data reflects biased patterns (and most data does), the AI’s recommendations will reproduce those biases. Steve draws a parallel to the pharmaceutical industry: AI needs regulation and oversight, not blind trust.
AI can’t care. As work shifts from repetitive tasks to roles that require exceeding expectations, solving novel problems, and making people feel valued, the caring dimension becomes more important. AI can automate the repetitive parts of L&D work, but it can’t replicate the human elements that make development meaningful.
What should L&D leaders do about it?
Steve’s practical advice for L&D professionals:
Experiment now, don’t wait. Organizations need to become early adopters rather than waiting for AI to mature. The learning curve for effective AI use is real, and the teams that start experimenting today will be years ahead of those that wait.
Find your “true HR professionals.” Look for people on your team who are genuinely excited about technology and give them room to explore. They’ll become your internal champions and guides.
Show, don’t argue. To convince leadership to invest in AI tools, provide concrete examples of how AI solves specific business problems. A successful pilot with measurable results beats a hundred slide decks about AI’s potential.
Focus on effectiveness, not familiarity. Organizations tend to buy technology that looks like what they already use. Instead, ask: “What would the most effective approach look like, regardless of what we’re used to?” Sometimes that means an AI coaching platform instead of another LMS.
Rethink how you evaluate expertise. AI can identify that a high school teacher has similar underlying skills to a store manager. As AI gets better at mapping transferable skills, L&D leaders should reconsider rigid job requirements and look at capability potential instead.
The bigger picture
Steve makes a point that often gets lost in AI conversations: humans are wired for change and learning. It’s organizations that become resistant to change as they grow. AI doesn’t threaten the human capacity to learn and adapt. If anything, by automating repetitive tasks, it frees people up for the uniquely human work of imagining, creating, and caring for others.
The L&D teams that will thrive aren’t the ones that use the most AI tools. They’re the ones that clearly understand what AI is good at (pattern recognition, automation, scale) and what requires human judgment (strategy, empathy, ethics, culture). Then they build workflows that put each in the right role.
Meet the host
Ashish is an entrepreneur tackling workplace development challenges through Risely, an AI copilot that helps managers and leaders build essential people skills.
Connect: LinkedIn