Built in, not bolted on
Most organisations are adding AI to software that was never designed for it. The real gains come when AI is part of the architecture, not an add-on to it.
A chatbot surfaces above an old document repository. A copilot attaches itself to fragmented data. A smart search layer sits on top of years of accumulated disorder. The AI works, up to a point. Then it runs into the same wall every time: the information underneath it.
The problem underneath
When people talk about AI disappointing them, they usually mean the model. The output is generic, the answers are wrong, the assistant keeps missing context. But the model is often not the issue. What it has to work with is.
Most organisational knowledge still lives in SharePoint folders with inconsistent naming, email threads where decisions disappear, documents that exist in four versions with no clear indication of which is current. Add a copilot to that environment and you get a faster, more articulate reflection of the same confusion. The AI amplifies what is already there. If the structure is weak, the results are weak.
Architecture first
Built-in AI assumes that information has structure, that documents carry provenance, that workflows are legible enough for a system to participate in them. Not a large IT replacement project. A different starting point.
Knowledge work organisations that are getting real results from AI tend to share one thing: they treated the information architecture as part of the AI investment, not a precondition someone else would handle. That means version control that is actually used, consistent tagging, clear ownership of documents, workflows that do not rely on institutional memory to navigate.
A well-structured knowledge base is useful long before any AI touches it. The AI just makes the gap visible faster.
The compliance accelerant
In regulated sectors, the pressure is sharper. When an adviser needs to reconstruct a recommendation from three years ago, or a regulator asks which version of a policy was in force on a given date, the question is not whether the AI can answer it. The question is whether the information environment can support the answer at all.
AI governance and information governance are converging. Organisations that have separated the two, running AI initiatives on top of legacy information infrastructure, will encounter this collision eventually.
The question that shifts
For a while, the distinguishing question was "do you have AI?" Now it is closer to "is your organisation built to work with it?" A copilot on top of a well-structured environment is a genuine productivity multiplier. The same copilot on top of a fragmented one is a better interface to the same old problem.
The architecture was always the work. AI just made the cost of skipping it more visible.
Rob Hoeijmakers
Rob Hoeijmakers
Rob Hoeijmakers
Rob Hoeijmakers