The question that starts it
At the end of an otherwise routine board meeting, a non-executive asks what the organisation's AI strategy is. The CEO gives a competent holding answer and promises a paper for the next meeting. By Monday the request has become a project: the strategy director owns it, a consultancy has offered a two-week accelerator, and three vendors who read the same market signals have found reasons to get in touch. Nobody has yet named a business problem the strategy is supposed to solve, and the deadline is now set by a board calendar rather than by anything happening in the operation.
Why the honest answer is hard to write
Every incentive in the chain points towards a confident document. The CEO needs the board reassured, not educated in ambiguity. The strategy team is judged on the quality of the paper, not on what gets deployed eighteen months later, and a paper full of caveats reads as weakness. Consultancies can produce an impressive AI strategy for any client because the genre has conventions: a maturity model, a capability heatmap, a portfolio of use cases, a roadmap in waves. The board, for its part, rarely has the technical depth to distinguish a deployable plan from a plausible one, so the document gets graded on coherence and confidence. A paper can satisfy every party in this chain and still commit the organisation to nothing real, which is precisely the risk.
What the applauded paper costs later
The gap between the deck and the operation surfaces on a delay, and by then the deck has been approved.
- Pilots launch in every function because the roadmap promised breadth, and none has an owner accountable for moving a business number.
- Platform and licence spend gets committed before any use case has proved it needs that platform.
- A capability slide assumes talent the organisation has not hired and, at current compensation, cannot.
- Governance and data questions are deferred to "phase two", then rediscovered mid-deployment as blockers.
- A year on, the same non-executive asks what happened to the strategy, and the honest answer is that it was presented.
Questions that turn the request into a decision
- Which three business problems, named and owned, would we want solved even if AI did not exist?
- What did the organisations behind the announcements the board has read actually deploy, and what has it changed in their numbers?
- What can our data actually support today, verified by someone outside the team that manages it?
- What are we already spending on AI across functions, counted honestly, and what has that spend returned?
- What would we stop doing to fund this, and who has agreed to stop it?
Pressure-test the paper before the board sees it
The most useful test is to strike out every sentence that could appear in a competitor's AI strategy unchanged. What survives is your strategy; the rest was genre. Then test the first commitment specifically, because boards approve directions but organisations spend money on first steps: is the initial use case chosen for feasibility and measurable value, or for visibility? Test the talent assumption against the actual hiring market rather than the organisation chart the deck imagines. And decide in advance how the board will be told about failures, because a programme that cannot report a failed pilot will keep failing pilots alive to protect the story.
Who should shape the answer before it is presented
Internally, the paper needs authors beyond strategy: the CIO and data owners on what the estate can support, function heads on which problems are real, finance on what the current scattered spend already amounts to. Externally, vendors and consultancies will contribute enthusiasm with an invoice attached. The perspective that is genuinely hard to buy is from executives who have taken an AI strategy through a board and into deployment: they know which promises survived contact with legacy systems and which slides they came to regret. Selected senior operators from the Global Board can review the paper before the meeting and tell you which parts a board would applaud and which parts an operator would question. That rehearsal is worth more than another framework.
