AI Consulting
AI Readiness: A Practical Checklist Before Your First Pilot
A practical way to test whether an AI opportunity has the sponsorship, data, governance and adoption conditions it needs.
Why this matters
Technology projects create value when they are tied to a clear user need, reliable information, appropriate controls and an operating model that continues after launch. This guide is written as a practical starting point for a discovery conversation.
Use the questions below to expose assumptions early and to decide whether the opportunity is ready for a prototype, needs foundational work, or should be deprioritised.
Practical checklist
- Start with the decision or task, not the model
- Check whether the required knowledge is current and owned
- Define who reviews uncertain or high-impact outputs
- Agree how usefulness will be measured
- Plan ownership after the pilot
Keep the first release narrow enough to evaluate with real users, but complete enough to test the end-to-end workflow.
What to do next
Document the current process, name the owner, define the desired outcome and gather representative examples. That evidence gives business and technical teams a much better starting point than a product demonstration alone.
Discuss your use case