Are we preparing knowledge for AI, or thinking too small?

I keep hearing that the AI era requires Knowledge Managers to invest heavily in making organizational knowledge “AI-ready”: cleaning it, curating it, tagging it, structuring it, improving metadata...

I’m skeptical.
My assumption is that AI will increasingly learn to deal with the mess.
And until it does, we can help it. We can instruct it to prefer newer versions over older ones. To flag contradictions rather than silently choose between them. To consider source authority, context and recency. And we can embed these and other smart instructions into the way our AI systems work.
Think about Google. Even 20 years ago, it managed to deliver remarkably useful results from an Internet full of outdated, duplicated, contradictory and simply bad content.
AI will become much better at doing the same.

So why does this concern me?
Because if Knowledge Managers define their future around cleaning, tagging and preparing content for AI, we risk two things:
1️⃣ Underestimating the enormous potential of the technology itself.
2️⃣ Reducing Knowledge Management to a kind of sophisticated content maintenance function.

I believe our future is much bigger than that.
Yes, Knowledge Management needs to reinvent itself in the AI era. But not by becoming better content technicians.
We need to reinvent ourselves at a much more strategic level, using AI to do things with organizational knowledge that weren't possible before.

How?
I don’t have one neat answer. But I definitely see some exciting directions.
And they deserve a series of posts, rather than one very long one 😊
Because knowledge is both the oxygen and the diamonds of every successful organization. In the AI era, this becomes even more true, not less.

The opportunity for Knowledge Management is enormous.
We just need to aim high enough.
More to come. Stay tuned.