What an AI strategy decides
| Element | What it sets | A question it answers |
|---|---|---|
| Decision | Which AI work to fund, in what order, and what to stop | Which initiatives get funding first? |
| Owner | Who answers for each result | Who owns the change to this workflow? |
| Measure | The change in revenue, cost, time or risk each investment must show | What baseline will the result be measured against? |
| Control | The approvals, limits and stop conditions that apply | What would make us stop this project? |
Our guide to how to build an AI roadmap explains how the strategy becomes sequenced work. The AI Roadmap is the engagement that produces it. For the controls, read the library on AI management and governance.
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Frequently asked questions
What should an AI strategy include?
Beyond the 4 elements in the table, include the evidence each decision rests on. That means a baseline for every measure and an honest view of the data and governance the work depends on.
What is the difference between an AI strategy and an AI roadmap?
The strategy sets which AI work is worth funding and why. The roadmap turns it into sequenced work: what you will do, in what order, under whose ownership and controls. Our guide to building an AI roadmap explains the decision gates.
How long does an AI roadmap take?
Most roadmaps take 4 to 8 weeks, depending on the number of business units and decisions involved. The AI Roadmap sets out the 5 phases.
The first conversation applies these articles to your own funding, ownership and measurement decisions.