More Content, Less Learning

My number one talk from the second day of the World Economic Forum's New Champions sessions was called "More Content, Less Learning." I keep coming back to it because it named something I see all the time in workplace training, and now especially with AI.

The panelists challenged the assumption that greater access to information automatically leads to better learning. Even when the best content is accessible, material change does not happen. That sounds obvious once you say it out loud. Yet so much of what organisations do still rests on the opposite belief: put the material in front of people, track completion, and expect capability to follow.

One speaker put it simply. Learning is not just watching, listening or reading. Learning is about doing, and doing is hard. He compared it to going to the gym. You can have excellent videos on every exercise and still leave unchanged if you never pick up the weight. Another panellist talked about the old transmission model of education: stuff enough knowledge into someone's head and hope it sticks. It does not. Students, he said, often want something hard, but hard with purpose. They know they need friction if they are going to learn.

That landed for me because it cuts against the way AI is often sold into organisations. We make it easier to get answers, easier to produce drafts, easier to summarise a course into three bullet points. Useful, yes. But if we are not careful, we also make it easier to skip the awkward middle bit where someone has to try, get it wrong, and try again. You can feel informed without being able to do the work.

The session was not anti-technology. The point was more careful than that. Tools help when they sit inside a proper learning process: practice, feedback, a reason to put the effort in. Hand people content and leave them to it, and outcomes stay thin. That is true of edtech platforms, and it is true of corporate AI rollouts that confuse licences and modules with change.

So what should we do differently? Protect time for learning instead of bolting modules onto an already full week. Lighten the load while people are training, and for a bit afterwards while they apply what they have learned. Ask whether someone can do the task differently tomorrow, not whether they finished the video. And design AI training around doing: rewrite the prompt, challenge the output, change a real workflow, defend a recommendation.

Learning requires friction, effort and critical thinking. It needs people to engage with the information, not pass through it. Content is easy to buy; learning is harder, and that is where the real investment belongs.