Month: April 2026

The primary reason boards terminate AI initiatives prematurely is a fundamental misunderstanding of how value accumulates. Traditional financial models are built to measure “intercepts”—static points in time that show immediate cost savings or productivity gains. However, AI does not behave like a traditional software purchase. Success is determined by...

The prevailing narrative suggests that AI failure is a 'change management' or 'emotional' problem. In reality, this is a mechanical failure of implementation. Resistance is rarely emotional, it is usually a rational response to broken process logic. When a generative AI tool is 'bolted on' to a manual process,...

Part of the series: AI at the Wrong Speed The organisations that will define enterprise AI over the next decade aren’t necessarily the ones with the largest implementation budgets or the most aggressive deployment timelines. They are the ones that are, right now, doing work that is largely invisible:...

"A P&L figure tells you where the organisation stood at measurement. It says nothing about where it is heading."...