4. Delivery¶

1. Purpose¶

The system is production-ready. Now it must be deployed safely: user training, human-in-the-loop protocols, an emergency stop culture, and a formal handover to the operations team. The result: an operational AI system that is technically integrated, humanly controlled, and broadly accepted.

Entry criteria: Phase 3 complete, all tests passed, infrastructure ready, implementation team on standby.

2. Components¶

• Overview & Objectives — What this phase aims to achieve
• Activities — Go-live planning, training, human oversight protocols
• Deliverables — Deployment checklist, handover documentation
• Traceability — Linking goals to implementation and evidence
• Adoption Management — ADKAR framework for AI adoption and resistance analysis
• Handover Checklist — Template for formal handover

3. Common pitfalls¶

• Skipping user training — a technically perfect system fails without trained users
• No emergency stop protocol — define upfront who can shut down the system and when
• Handover without documentation — the operations team must be able to act independently
• Rolling out too fast — start with a limited group of users and scale gradually

Next step: After go-live, proceed to Phase 5 — Monitoring & Optimisation.