Pick use cases with real data
AI should not start with the model. Start with repeated work, where data lives, and how risky mistakes are.
- Repeated work
- Available data
- Low-risk pilot
- Clear owner
AI Enablement
AI workshops should end with pilots, not pretty slides
A useful AI workshop produces use cases, selects one or two small pilots, identifies required data, and defines success criteria.
8 min readSet guardrails early
An AI pilot needs to know when it can answer, when it lacks data, and when it should hand off to a human.
- No fabrication
- Clear sources
- Human fallback
- Answer logs
Measure behavior
A fun demo is not enough. Measure handled tickets, time-to-answer, follow-up questions, and whether staff actually use it.
- Adoption
- Time-to-answer
- Deflection rate
- Human review