Is L&D's role expanding in the age of AI?

A huge amount of learning has always happened outside formal courses, and todayAI has made that visible and measurable for the first time. When someone can ask an AI assistant "how do I do X" and get a contextual answer inside their actual tool, that's a learning event L&D never touched, never tracked, and never designed. It just happened. That's a real expansion of the addressable surface.

Has AI changed how people learn day to day?

In short: Yes. AI has shrunk the gap between "I don't know how to do this" and "I did it" to almost nothing. People learn by asking mid-task instead of scheduling training. That's faster, but riskier: getting a quick answer can feel like learning without actually building a durable skill, since the struggle that makes things stick often gets skipped. It's also made learning more reactive, triggered by whatever you're doing right now: which is great for relevance but can crowd out the kind of open browsing where people used to stumble onto skills they didn't know they needed. So the real question for L&D isn't "did AI help people get answers faster": it's "did that moment leave them more capable next time, or just unblocked this time."

Has it changed what your L&D team spends the most time on?

I am not part of a larger department with multiple L&D and ID roles. However, the change I would recommend is spending less time producing content from scratch and more time on review, judgment, and governance. AI now drafts a lot of the first pass: outlines, quiz questions, scripts. So the work would shift from "write it" to "check it's accurate, on-brand, and actually teaches the right thing." At the same time, new work has appeared that didn't used to exist: vetting AI tools, setting data/guardrail policies, and figuring out how to measure whether learning embedded in workflows is actually working, not just whether a course got completed.

Where do you see the biggest opportunity, or challenge, for L&D right now?

The biggest opportunity is that L&D can finally tie learning to real outcomes measuring whether skills got applied, not just whether courses got completed. The biggest challenge is that AI adoption is outpacing the infrastructure and governance to support it, while the skills people need keep changing faster than L&D's operating model was built to handle. So it's less "build more courses" and more "build the systems to know what's working, wherever learning happens."

The future opportunity is not just using AI to make more courses. It is building self-improving learning ecosystems that continuously collect signals, analyze them, and adapt in real time. A possible future state looks less like an LMS and more like a Learning Intelligence Platform.