AI is everywhere. Every conversation in L&D right now seems to include AI. And yet, for all the talk about smart tech, there’s one thing we’re still not talking about nearly enough: what actually changes at work after the learning?
That old elephant in the L&D room, learning transfer, hasn’t gone away.
Let’s be honest. Most learning programmes still assume that if people access content, they’ll somehow perform better. And AI can certainly build content for us. But learning isn’t about ticking off a course. Real learning, the kind that leads to behaviour change, is what happens after the training, back in the flow of work.
We know this. And yet we keep designing as if content consumption equals results.
So what does learning transfer look like?
At its core, learning transfer is a messy, human process. It often involves:
• Gaining information
• Applying it in real work
• Getting feedback
• Reflecting
• Adjusting
• Repeating until it sticks
It’s not always linear. It doesn’t always look neat on a slide. But it’s how people actually learn to do something new.
The real challenge is supporting this process, all of it. Not just the first step.
And yes, technology can help. Used well, tech can support each stage of the cycle. But used badly, it can just as easily sabotage learning by removing the very effort and thinking required to change. When platforms do the thinking for us, they become part of the problem.
There is an old aphorism in education: ‘The person that does the thinking gets the learning’.
So here’s the call to action: let’s put learning transfer back at the centre of L&D. Let’s design for behaviour change, not just content delivery. And let’s use our tools, AI included, to support real human learning, not distract from it.
Because in the end, it’s simple: if people aren’t doing something different, they haven’t really learned.
