In the rush towards AI, have we forgotten human curation?
AI can find and catalogue. But can it truly curate learning?
More content is not the same as more learning
One of the risks with AI is that it can make the content problem worse before it makes it better.
We can now create more content, more quickly, in more formats, for more audiences. That sounds useful. And sometimes it is.
But if the problem is already too much content, too many platforms, too many links, too many recommendations and too little clarity, then simply adding more will not solve it. In fact, it may do the opposite.
Learners do not just need access to information. They need help understanding what matters. They need to know where to start, what to ignore, what to trust, what to do next and how it connects to the work they are trying to do.
That is where curation becomes important. Because the future of learning is not just about creating more, faster.
It is about helping people find what matters, when it matters, and understand what to do with it.
AI can find content. But can it curate learning?
What AI can do well.
AI can help with a lot of the heavy lifting.
It can:
- Search across huge volumes of information.
- Summarise articles and long-form content.
- Generate lists of resources.Compare sources.
- Suggest themes and structures.
- Recommend content based on a topic, role or skill.
That can save a huge amount of time.
But it is not the whole job.
What curation still needs.
Real curation means asking better questions.
- What problem are we trying to solve?
- Who is this for?
- What do they already know?
- What do they need to do differently?
- What is credible enough to use?
- What should come first?
- What should be left out?
- Where does support, practice or reflection need to sit around the content?
That is where human judgement still matters.
Where L&D adds value.
Curating learning still requires judgement.
It’s not just:
- A list of resources is not a learning experience.
- A content library is not a pathway.
- A recommendation engine is not the same as understanding the business, the audience, the context and the desired outcome.
Human input:
- Someone still has to decide what matters.
- Someone still has to turn information into learning.
- Someone still has to create the thread that connects content to performance.
It’s not L&D versus AI. And it’s not human judgement versus automation.
AI should be doing heavy lifting, so L&D can spend more time on the work that actually creates value.
Curating judgement and judgement is exactly where L&D should be leaning in.
What good content curation actually involves
Good curation is not just collecting resources.
It is the deliberate work of turning information into something useful.
It starts with business and learning needs
Good curation is not a folder of links, a content library, or even a platform full of “recommended for you” assets.
So the starting point should not be:
- What content do we have?
- What can AI find?
- What can we add to the platform?
There is often an assumption that the platform will do more of the work than is realistically possible.
It should be:
- What problem are we trying to solve?
- Who is this for?
- What do they need to do differently?
- What will help them act, decide, practise or improve?
It becomes learning design when you shape it
One useful way to think about content curation is as a process.
- Aggregation brings useful resources together in one place.
- Distillation reduces the noise and keeps only what is relevant, credible and useful.
- Evaluation checks quality, accuracy, relevance, accessibility and fit.
- Combination connects different resources so they become more meaningful together than they are on their own.
- Chronological organisation sequences content so it supports progression, rather than leaving people to browse and hope for the best.
That is where curation starts to become learning design, not just about finding content. Your judgement and expertise starts shaping it into something useful.
Start with the problem, not the content.
The starting point should not be the content. It should be the problem.
- What problem are we trying to solve?
- What is happening in the organisation?
- What needs to improve?
- What do people need to understand, decide or do differently?
- What is getting in the way?
Not understanding your content risks building beautifully organised collections that don’t really solve anything. It’s the danger of curation becoming too platform-led or too AI-led.
The platform can hold the content. AI can help find it.
But L&D still needs to understand the reason it is there.
A practical checklist for better curation
Before going to market, it’s worth stepping back and asking a different set of questions:
- Start with the performance problem, not the content.
- Know the audience and their context.
- Filter hard.
- Add explanation: why this, why now, and how to use it.
- Sequence content into a useful journey.Keep it practical and easy to access.
- Review, refresh and retire content regularly.
- Use AI to speed up the work.
- But do not outsource the judgement.
That last point is important. AI should do the heavy lifting. It can help us work faster and see patterns sooner.
But the role of L&D is not simply to produce more material. It is to help people make sense of what is available and apply it in ways that improve performance.