AI implementation is not a ChatGPT subscription or a one-time workshop. It combines process, information, technology, and adoption. Ninety days is enough to prove value in one process, but not to transform an entire organization.
Days 1 to 15: choose a problem
Collect repetitive workflows and select one with high volume, a clear outcome, and controlled risk. Document current labor time, error rate, and cost. Avoid rare processes and situations where one mistake creates irreversible harm.
Days 16 to 30: prepare a safe foundation
Map data sources, owners, and permissions. Decide what information must never reach an external provider and where human approval is mandatory. Create a test dataset and success metric before selecting the tool.
Days 31 to 60: pilot with real users
Build a narrow version and release it to a small team. Record inputs, outputs, corrections, and escalations with appropriate privacy controls. A short weekly session with users reveals problems analytics alone will miss.
Days 61 to 90: measure and decide
Compare results with the baseline. Review cost per task, completion rate, corrections, and adoption. The decision can be expansion, revision, or stopping. Ending a pilot that does not create value is a success of the process, not a failure.
Who owns the rollout
The team needs a business process owner, technical owner, and a person responsible for policy and risk. A large committee without an owner slows decisions. A developer without a process owner builds something nobody adopts.
The production gate
Before expansion, verify permissions, monitoring, costs, fallback providers, failure handling, audit logs, and user training. Only a use case that passes this gate should receive more data, autonomy, or users.