Enterprise AI

Most companies don’t fail at AI because of bad models. They fail because they never had a strategy. That might sound blunt, but it’s what shows up again and again in enterprise settings. Teams jump into pilots, experiment with tools, hire a few data scientists—and then stall. Not because the tech didn’t work, but because the system around it didn’t exist. If you’re leading AI inside an organisation, you don’t need more tools. You need structure. ...

Imagine asking your policy system a simple question and getting a perfect answer in under a second. Now imagine asking it to analyse fifteen years of reports, submissions, evaluations, and operational metrics. One requires a chatbot. The other requires an engine. Policy teams often reach for RAG because it looks neat and tidy. A chatbot that can trawl internal guidance, regulatory texts, consultation documents and memos feels like a small miracle. And to be fair, a well-tuned Retrieval-Augmented Generation system is a brilliant librarian. It fetches the right paragraph, summarises dense text, and saves you from spelunking through document drives that haven’t been organised since John Key was in office. ...

When I was in Year 6, my history homework was supposed to be full of long, serious answers. There were fifty kids in the class, and I remember wondering — does the teacher actually read every word? So, halfway through one answer, I slipped in a few lines from a song. My heart sank when I handed it in, expecting trouble. But when I got the copy back, there it was — a big red tick on that very page. I had, in some sense, hijacked the teacher’s chain of thought. ...