The AI debate in 2026 has become oddly binary. Either white-collar work shrinks dramatically and SaaS margins collapse. Or nothing much changes at all. The more interesting story sits between those extremes. In its February piece, Harvard Business Review argued that AI investments are not failing because the technology is weak. They are underperforming because organisations have not redesigned how work flows. Layoffs in some firms are outpacing realised productivity gains. “W

I was recently sent an article arguing that large language models are fundamentally limited. They predict the next word. They don’t truly “understand.” They hallucinate. Scaling alone won’t produce general intelligence. There’s truth in that. Transformers are probabilistic pattern learners. They lack grounded experience and intrinsic intent. Hallucinations are real engineering challenges. Scaling alone is unlikely to magically deliver AGI. But I think the debate often misses

This keeps coming up in conversations. Leaders expect AI to free up time. Teams report being faster. Yet nobody feels less busy. A recent Harvard Business Review article from February puts some structure around why. In an eight-month study of a mid-sized technology company, generative AI didn’t shrink work. It intensified it. Employees worked at a faster pace, took on broader responsibilities, and stayed engaged for more hours of the day. None of this was mandated. It happene