Choose an AI pilot that earns the right to scale.
Define the workflow, baseline, quality threshold, economics, and accountable operator before building.
Name the operating problem
Choose a repeatable workflow with a clear input, output, user, and exception path. Describe the business constraint before choosing the model or vendor.
Leave withA one-page workflow charter with scope and exclusions.
Define evidence and safeguards
Use representative examples with permission to process the data. Specify how output quality is scored, when a human must review it, and what the system must not do.
Leave withA test set, acceptance rubric, human-review policy, and escalation owner.
Model the real operating cost
Include setup, integration, licenses, inference, reviews, exceptions, maintenance, and adoption. Value time released separately from actual spending removed.
Leave withA baseline and sensitivity-tested business case.
Set the scale decision in advance
Run the pilot against the baseline, monitor exceptions, and record operator feedback. Scale only when business value and quality are sustained.
Leave withA documented scale, revise, or stop decision with operating ownership.
Make it specific to your business.
The agenda is a starting point. Company data, operating context, and the people doing the work determine the right next move.