In learning design, it’s easy to focus on the what and how — what content to deliver and how to get it across. But too often, the why gets lost along the way.

Without a clear purpose driving the process, learning initiatives risk becoming more about ticking boxes than driving change. And when technology enters the mix, the lines can blur even further. Are the tools enabling better learning experiences — or just adding noise?

This distinction matters more than ever, especially when trends and tools start to take the spotlight.

The AI Hype and the Human Factor

AI has been the hottest buzzword of the year, and corporate learning hasn’t escaped its grip. For the past two years, every learning convention has been flooded with AI-powered products—just like gamification before it, microlearning a few years back, and AR/VR in what feels like a distant past.

What all these trends have in common is that they’re solutions looking for problems. They shine in specific use cases, but the danger comes when we mistake the trend for the goal. The goal has always been the same: creating effective, behavior-changing learning experiences.

Take the recent hype around automated course creation. The claim? Feed raw data into an AI tool, and it’ll spit out a fully designed course in minutes. Revolutionary? Not quite. What you usually end up with is a glorified PDF—a polished dump of information, with no real instructional design behind it.

While AI excels at organizing content, does it inspire learners to think differently or act decisively? Hardly.

As Clark Quinn aptly puts it in one of his recent podcasts, “One of the biggest misconceptions is the belief that giving people information will change their behavior.” AI might churn out content faster than a coffee machine brews espresso, but creating meaningful, behavior-focused learning experiences is still a job for humans.

What AI Gets Right (and Where It Trips)

AI is brilliant at doing what it’s built for: handling repetitive, data-heavy tasks with speed and precision. It can analyze performance data, highlight gaps, and even suggest personalized learning paths. It can distill dense policy documents into readable summaries, saving hours of manual effort.

But here’s the thing—these are enablers, not solutions.

AI can lay the groundwork, but it can’t design a meaningful learning experience on its own. Good learning design starts with the right questions: Who is this for? What should they be able to do after training? What mistakes or misconceptions get in their way? Where will they apply what they’ve learned?

And this is where empathy becomes critical.

As Julie Dirksen points out in Design for How People Learn, empathy in learning isn’t about making people feel good—it’s about understanding how they think. It’s about knowing where learners are likely to get stuck and addressing those friction points. AI might pull together content, but it takes a human to ask, “Will this actually work?”

Dirksen also highlights that learners often avoid new behaviors not because they lack information, but because they lack confidence. AI can flag errors, but it takes a skilled designer to frame feedback in a way that encourages progress, builds self-efficacy, and creates a safe space to try, fail, and try again.

Empathy ensures learning doesn’t just inform—it transforms. And that’s something no algorithm can replicate.

AI Isn’t the Pilot—It’s the Wingman

AI can automate tasks, suggest pathways, and generate content—but it can’t tell you if any of it actually works. That requires human judgment. It’s the learning designer who asks, What’s missing? What’s confusing? What’s holding learners back from changing their behavior?

And that’s where empathy makes all the difference. Understanding the emotional and cognitive barriers learners face is what turns a training session into a real behavior-changing experience.

The future of learning design isn’t about AI taking over—it’s about AI enabling better human-led decisions. AI isn’t the one flying the plane. It’s the wingman—there to offer insights, steer you out of turbulence, and help you get to your destination faster.

Get that balance right, and AI stops being a threat. It becomes the best partner a learning designer could ask for.

Sources

• Insights from Clark Quinn, shared on his blog Learnlets and The Brand Called You podcast.
• Key ideas from Julie Dirksen’s book Design for How People Learn and her blog Usable Learning.