Every AI project has a moment — usually somewhere between the enthusiastic kick-off workshop and the first sprint — where the organisation has to make a real decision.

Not the budget approval. Not the vendor selection. Not the architecture review. Those are necessary, but none of them are the decision that determines whether the project actually succeeds.

The real decision is the Go/No-Go gate at the close of Phase 1.

Most AI projects don't fail because the technology didn't work. They fail because nobody asked the right questions before the project started.

"So — what should we use AI for?"

It sounds like a simple question. It isn't. And the reason most organisations struggle to answer it isn't lack of ambition or budget. It's that "AI" has become a single word standing in for an enormous family of fundamentally different technologies — each with different requirements, different risks, and different definitions of success.