Generative AI

The biggest change in AI over the past few years may not be the quality of the output. It may be the quality of the interaction. What happens when working with AI starts to feel less like prompting and more like conversation?

Deloitte. Sullivan & Cromwell. Now EY. Three organisations, three contexts, the same essential failure. At some point, the pattern becomes the story – and the story isn't about AI hallucinations.

Everything was in place – policies, training, guardrails. And still, AI errors slipped through. This isn’t a technology failure but a human one. Perhaps the answer is simple: someone must own verification.

I've been deep in ChatGPT since 2022. Now I'm running a deliberate, staged experiment with Claude Pro – and one feature in particular, Cowork, has genuinely surprised me. It has my full attention as I continue working it out.

A New York Times review, an AI tool, and a missed check. The result wasn’t just overlap with another review – it was a lapse in process. A simple reminder: if AI touched it, you must verify it.

The question “Was this written by AI?” misses the point. What matters is whether content is accurate, useful, ethical, and purposeful. This post explores why judgement, not detection, is the responsibility communicators can’t outsource.

When a university professor lost two years of academic work after a single change to ChatGPT's settings, the lesson was stark. If the work matters, backups are your responsibility. ChatGPT is not an archive – and convenience is no substitute for protection.

Ads in ChatGPT aren’t the real story. Trust is. As OpenAI begins testing advertising, the challenge isn’t revenue or relevance, but whether users continue to believe the system works for them, not just for advertisers.