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AI Is Not the Problem. AI Readiness Is. Across every industry, Boards are investing heavily in AI to improve productivity, performance, customer experience, operational efficiency, and shareholder returns. AI has become a Board-level mandate. Organisations are expected to embrace it, competitors are already deploying it, and investors increasingly expect to see measurable AI-driven advantage. Yet despite the enthusiasm, many AI initiatives fail to meet expectations. The reaso

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.

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!

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

If you’ve been following the AI boom, you’ve probably heard the term Vector Database tossed around. It sounds like something straight out of a physics textbook, but it’s actually the "secret sauce" making modern AI - like ChatGPT or advanced recommendation systems - work so efficiently. But what are they, and why should you care? Let’s break it down without the jargon. What is a Vector Database, anyway? Traditional databases (the ones we’ve used for decades) store informatio