/04AI Strategy
A department-by-department AI strategy that answers what to buy, what to build, who owns it, what it costs, and what comes first.
Leader
14 min
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AI Strategy
A department-by-department AI strategy that answers what to buy, what to build, who owns it, what it costs, and what comes first.
Leader
14 min
Strategy is a sequence of choices under constraints. If your AI strategy is a list of tools, it is a shopping list.
Leave knowing / Turn AI ambition into an operating plan
Framework vs strategy
The framework shows where AI could fit. Strategy decides what the company will actually do, in what order, with what money, with whose ownership, and with which tradeoffs.
A good strategy says no to most possible AI projects so a few important ones can become real.
Where AI fits is analysis. What we do next is strategy.
Strategy stack
Make five decisions in order.
1. Business outcome
Name the customer or business result. Faster close, fewer support delays, shorter cycle time, better conversion, lower rework.
2. Workflow
Choose the exact repeated work that produces or blocks that outcome.
3. Product decision
Use existing software, configure a platform, build a custom system, or keep the process human.
4. Ownership
Name a business owner for the outcome and a technical owner for the system. Never leave AI owned by "innovation."
5. Evidence and expansion
Define the pilot metric, review date, failure condition, and what would justify expanding to the next workflow.
Per department
The strategy question changes with the work.
| Department | Strategy question | Useful proof |
|---|---|---|
| Sales | Does AI improve seller time or buyer movement? | Prep time, follow-up speed, conversion, CRM completeness |
| Marketing | Does it increase useful output without lowering distinctiveness? | Cycle time, approved output, performance, rework |
| Customer Success | Does it improve response without hiding risk? | Resolution time, escalation accuracy, satisfaction |
| Operations | Does it remove handoffs or just add another layer? | Touches per case, cycle time, exception rate |
| People | Does it reduce admin while protecting human judgment? | Admin time, completion, error or escalation rate |
| Finance | Does it improve preparation while preserving control? | Close time, review time, exception accuracy |
| Product | Does it shorten learning loops? | Research cycle time, evidence coverage, decision speed |
| Engineering | Does it increase verified throughput? | Cycle time, test quality, review burden, incidents |
Strategy page
Your AI strategy should fit on one page before it becomes a roadmap.
Three business outcomes AI is allowed to support.
Three first workflows and why they come first.
What will be bought, configured, built, or deliberately not automated.
A named business owner and technical owner for every live system.
Data, security, legal, and human-review boundaries.
Budget range and the cost of operating the system after launch.
A 30, 60, and 90-day evidence plan.
A stop condition for pilots that do not produce value.
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