Knowledge Is Becoming Infrastructure

I recently discovered that NASA has a Chief Knowledge Officer.

I may have felt a little too pleased about this.

Knowledge has become central to my work, and to what we are building at Schmuki. And for some time I have been making what can occasionally feel like an embarrassingly earnest argument: organisations need to start treating their knowledge as a strategic asset.

Not as a SharePoint problem. Not as document management. And not as the digital cupboard where everything goes once a project is finished.

So discovering that NASA has someone with knowledge literally in her title felt like a small moment of vindication.

Apparently, knowledge management really is rocket science.

Knowledge management had an image problem

Knowledge management is hardly new. Organisations have spent decades building taxonomies, intranets, document-management systems and knowledge bases.

But it has often lived slightly apart from the organisation itself.

There was something almost library-like about it. Specialists classified information, designed structures and tried to persuade everyone else to document what they knew. Maintaining those structures required a great deal of human labour, while the organisation itself kept changing.

The result will be familiar to almost anyone who has worked in a large organisation: elaborate information environments that gradually drift away from reality. The SharePoint site nobody quite trusts. The policy document that may or may not still apply. Several versions of the same process. Knowledge trapped in people’s heads, inboxes and project folders.

That was already a problem.

AI makes it a different kind of problem.

AI works from knowledge

A language model brings an extraordinary general capability to interpret, reason and generate. But it doesn’t automatically know your organisation.

It doesn’t know what you have decided. What your current policies are. Which products you offer. What you promised customers. How a particular regulation applies to your work. What was learned from the last project. Which version of a procedure is authoritative.

For AI to become genuinely useful inside an organisation, it needs the right material to reason from.

That changes the value of organisational knowledge.

A knowledge base is no longer primarily something we maintain in the hope that an employee might search it one day. It increasingly becomes part of the grounding layer for systems that answer questions, support decisions and, as we move towards agents, take actions.

Put an intelligent agent on top of a chaotic information landscape and you haven’t solved the information problem.

You may simply have accelerated the chaos.

But AI also works on knowledge

This is the other half of the change, and I think it matters just as much.

The same AI that needs well-organised knowledge can help us create and maintain it.

It can classify documents, restructure information, compare versions, extract entities, identify contradictions, connect related material, detect gaps and help determine what needs updating when the outside world changes.

That matters because knowledge has always had a maintenance problem.

Organisations aren’t static. Laws change. Products change. People leave. New decisions are made. Terminology evolves. Experience accumulates. A beautifully organised knowledge base begins ageing almost as soon as you finish it.

AI changes the economics of that maintenance.

It makes organisational knowledge easier and cheaper to maintain at precisely the moment when well-maintained knowledge is becoming more valuable.

That creates a flywheel.

AI works on knowledge. Better knowledge gives AI better material to work from. Using AI creates new experience and knowledge, which can in turn improve the knowledge system.

Knowledge stops being an archive of the organisation and starts becoming part of its living infrastructure.

From knowledge to wisdom

There is another step beyond this.

An organisation isn’t simply a collection of facts, documents and rules. It also contains experience about how those things should be applied.

Two organisations can operate under exactly the same legislation and behave quite differently. A written policy rarely captures every exception, consideration or judgement that experienced people make when applying it.

That distinction becomes increasingly important as AI moves from finding and generating information towards supporting decisions and taking actions.

Knowing the rule is knowledge.

Knowing how this organisation responsibly applies that rule in a particular situation is closer to wisdom.

That is considerably harder to capture. But it may also become one of the most valuable things an organisation possesses.

Back to the boardroom

This is why I think the status of organisational knowledge is changing.

AI didn’t suddenly make knowledge valuable. Organisations have always depended on what they know.

But AI is making that value much harder to ignore.

If knowledge is becoming both the material AI works from and the material AI works on, it seems increasingly strange to treat it primarily as an IT housekeeping problem.

It is intellectual capital. It is AI infrastructure. Increasingly, it is part of the operating model of the organisation.

That doesn’t mean every organisation needs to appoint a Chief Knowledge Officer tomorrow.

But somebody needs to be responsible for a deceptively simple question:

Does the organisation actually know what it knows?

NASA, at least, has decided that question deserves serious organisational attention.

I confess I find that rather reassuring.

And perhaps a little vindicating.

The company does not live in the LLM

A knowledge-intensive company should keep durable organisational knowledge outside the model, and let AI do what it is unusually good at: reason across it.

Rob HoeijmakersRob Hoeijmakers