Setting Up Pilot Projects Right
An AI pilot is not an experiment — it's a structured project with a clear goal. Most pilots fail not because of technology, but because of poor setup.
The Perfect Pilot Scope
What makes a good pilot:
- Clearly defined use case — one process, one team, one outcome
- Measurable success criteria — defined before start
- Limited timeline — maximum 12 weeks
- Realistic expectations — 80% solution is enough for proof
- Clear production path — what happens after the pilot?
What makes a pilot fail:
- "Let's test AI" (no concrete goal)
- Too many stakeholders, too little decision-making power
- No budget for after the pilot
- Isolated innovation lab without business connection
The Pilot Template
1. Problem Statement (1 page)
WHAT is the problem?
WHO has the problem?
HOW MUCH does it cost us today?
WHY can AI help?
2. Success Criteria (3–5 KPIs)
| KPI | Baseline | Target | Measurement |
|---|
| Processing time | 15 min | <5 min | System logs |
| Error rate | 8% | <3% | Sampling |
| Employee satisfaction | 5/10 | >7/10 | Survey |
3. Team (5–7 people)
- Product Owner (business side) — defines requirements
- AI/ML Engineer — builds the model
- Data Engineer — prepares data
- UX/Frontend — designs the user interface
- Domain Expert — validates results
- Executive Sponsor — removes obstacles
4. Timeline (12 weeks)
| Week | Phase | Deliverable |
|---|
| 1–2 | Discovery | Problem validated, data reviewed |
| 3–4 | Data Prep | Data cleaned and structured |
| 5–8 | Build | MVP with core functionality |
| 9–10 | Test | UAT with real users |
| 11 | Evaluate | KPI assessment, lessons learned |
| 12 | Decide | Go/no-go for production |
5. Go/No-Go Criteria
- At least 2 of 3 KPIs met → Go
- User feedback positive (>7/10) → Go
- Production path clear and funded → Go
- Otherwise → Kill or pivot
Golden rule: A pilot without a go/no-go date isn't a pilot — it's a hobby project.