I first got into AI in the late 1980s while at Air Canada. At that time, AI research and applications were dominated by the languages LISP and Prolog. I experimented with both, and was fascinated with Prolog’s ability to solve problems that you defined as facts, and rules. During a recent visit to Bletchley Park north of London, I reflected on how this ability could have helped the tedious code-breaking efforts there, had it been available, and picked up a book of logic puzzles in the shop, with the intent of solving them using AI and Prolog.

Last week, I had the pleasure of presenting a keynote at the AI Consulting Conference 2026 in Munich, although I had to connect virtually from London due to other commitments. My key point is that AI is eating away at a lot of the magic powers that consultants used to wield, and that to stay relevant, you need to identify the gaps between what AI can do, and where experts are still needed. This is a moving target, and you need to understand something about how AI works to see where the gaps are.