A strong pilot candidate is performed regularly, has a clear beginning and produces an outcome that can be assessed. It may involve classifying requests, drafting document summaries or retrieving information from a controlled knowledge base. A poor starting point depends on exceptions, tacit rules or high-consequence decisions.
Choose a process, not an impressive demonstration
A demo shows that a model can generate an answer. A pilot should establish whether the solution works well enough in a specific environment: whether it uses the right data, respects permissions, remains economically viable and preserves human control where failure matters.
A pilot should lead to a decision
Before testing, agree a small set of criteria: output quality, total handling time including review, cost per case and the number of situations requiring escalation. A few successful responses should not be mistaken for production readiness.
A decision not to implement AI can also be a valuable pilot outcome. Sometimes simpler automation, better data or a process change solves the problem more effectively. The goal is to reduce uncertainty, not to validate a technology selected in advance.