From AI pilot to production: a practical guide
5 min read
Learn how to convert a successful AI pilot into a production environment with concrete steps.
From AI Pilot to Production: A Practical Guide
You've completed a successful AI pilot. The results are promising and management is enthusiastic. But then comes the question: how do we take this to production?
This is where most AI projects stall. According to McKinsey (2024), only 15% of AI pilots reach the production phase. The rest gets stuck in "pilot purgatory."
Phase 1: Evaluate Honestly
Before scaling, answer three questions honestly: Does it solve a real problem? Are users convinced? Is the data infrastructure scalable?
Phase 2: Build the Right Architecture
Production architecture differs fundamentally from a pilot. Key elements: separation of model and application, observability and monitoring, and proper security with RBAC and audit logging.
Phase 3: Strategic Rollout
Start with one department as early adopter. Train users, AI adoption is 70% a people problem. Define measurable KPIs: time saved, error reduction, user adoption rates.
Phase 4: Iterate and Optimise
Production is a starting point, not an endpoint. Plan monthly evaluation cycles: analyse usage patterns, refine the model, expand gradually, and keep stakeholders informed.
The Right Partner Matters
The pilot-to-production step is complex. An experienced partner provides technical expertise, change management support, compliance guidance, and ongoing management.
In the pilot phase and wondering how to scale successfully? Contact us or explore our consultancy offering.