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Where to start with AI when everything looks like a use case
A simple way to rank AI ideas by value, effort and risk — and to say no to the ones that only look impressive in a demo.
Most teams do not fail because they picked the wrong model. They fail because they picked a problem nobody owned, measured against nothing in particular.
Score three things, not twenty
Value: how much time or money is on the table each month. Effort: how much data plumbing stands between you and a working version. Risk: what happens on the day the system is confidently wrong.
Write the baseline down first
If you cannot state today’s number — hours per week, error rate, cost per case — you will not be able to prove the project worked. Capture it before you build anything.
Pick one visible workflow
A single workflow that a real team touches daily will teach you more about your data, your policies and your appetite for change than a year of strategy decks.
Topics
- Strategy
- Adoption
Services
- AI strategy & governance
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