The problem is usually invisible when the budget is committed.
That gap between what the business decided and what delivery actually builds is not visible at kick-off. It becomes expensive by the time it is. I have worked on 20+ projects across fintech, telecoms, energy, and the public sector — and the pattern is the same every time. The earlier it is found, the less it costs to close.
The numbers say the same thing: 95% of GenAI pilots yield no measurable ROI. Half of CEOs say they moved too fast and now have technology that does not work together. 60% of companies report little or no material value from AI despite substantial investment. The technology is rarely the reason. The business side of delivery — the decisions, the scope, the operating model around it — is where it goes wrong.
Sources: MIT NANDA, The GenAI Divide (2025, 300 deployments analysed); IBM CEO Study (2025, 2,000 CEOs); BCG (2025, 1,250 companies).