The strategy gap in AI

Walk into almost any leadership team today and you will find an AI pilot. A chatbot for customer queries, an assistant that drafts documents, a model that flags anomalies in transactions. Ask the same team which three decisions AI will change in their business over the next five years, and the room goes quiet.

This is the strategy gap. Organisations have mistaken activity for direction. Pilots are useful, but pilots chosen because they were easy to start rarely add up to an advantage that is hard to copy.

Start with decisions, not tools

The organisations that are pulling ahead begin with a different question: where in our value chain does better judgement, made faster and at scale, change the economics? Pricing, underwriting, scheduling, triage, and research are typical answers. The tool comes second.

This reframing also clarifies what must be true for AI to work: the data that has to exist, the people who must trust the output, and the governance that must be in place before anything reaches a customer.

Governance is an accelerator

Leaders often treat responsible AI as a brake. In practice, clear guardrails let teams move faster because they know where the lines are. The board’s job is not to approve every model, but to set the risk appetite and ensure the organisation can see what it has deployed.

Closing the strategy gap is therefore a leadership task. It requires executives who understand AI well enough to ask good questions, and an organisation designed to act on the answers.