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AI governance often fails in the same places: weak controls, poor knowledge, unclear ownership, and limited oversight. Here’s where AI systems break, and how to prevent it.

AI turns every organisation into a content factory, and most organisations were already struggling to keep their knowledge bases accurate before this wave hit. Now we are pouring petrol on it.

Everyone’s obsessing over the same question right now: “How do we get more people in the business using AI?” Because on paper it’s brilliant. It can bash out first drafts, summarise a mountain of info, untangle code, and generally take the boring weight off people’s shoulders so they can do the higher-value stuff.

Most organisations are treating “AI governance” like it’s a document-writing exercise. Write a policy. Form a committee. Add a disclaimer to the chatbot. Maybe run a training session. Job done. Except it isn’t. If you’re deploying AI in regulated or operational environments, the uncomfortable reality is this: compliance is going to be audited like finance . Not “do you have a policy?” but “show me the evidence.” And in practice, that evidence lives (or dies) inside your knowl

index is not “just an AI layer on top of your docs” If you’ve taken some time to look at what we do and thought, “Hang on… can’t we just add a copilot / RAG / search upgrade and call it done?”, you’re forgiven, because we've heard this a few times now - hence the blog post!

AI rarely fails because the model is “dumb”, it fails because the knowledge it’s pulling from is messy. If you’ve ever had an AI answer at work that sounded confident but made you think “hang on… is that actually true?”, you’ve hit the real issue: shaky inputs create shaky outputs. In this short video I explain why, in 2025/2026, enterprise AI is only as trustworthy as the knowledge base behind it, and why duplicates, contradictions and outdated docs quietly turn into errors,

AI Slop Is Everywhere. The Fix Is Not “Better AI”, It’s Better Provenance. You know what’s changed in the last year or two? It’s not just that AI can make content, it’s that it can make plausible  content at industrial scale, and the incentives online reward whatever gets clicks and shares. That might be harmless entertainment, but it becomes a serious issue the moment it influences business decisions, customer conversations, internal comms, or even what teams treat as “true”

Here’s the reality in 2025/2026: there isn’t one universal “where does AI gets its facts from?” because most frontier labs don’t fully disclose their training mixes anymore. But we can  anchor this in what’s publicly documented and what regulators/researchers keep pointing at. You know what people get wrong about AI? They think it “looks things up” like a clever librarian. Most of the time it doesn’t. Most of the time it’s answering from whatever got baked into it during trai