How to evaluate an AI agent pilot with Airlock

A practical AI email-agent pilot should test whether an agent can complete routine work safely and with meaningful time savings, rather than simply shifting effort to human approval queues or risking confidential disclosures. Using a workflow that reads Linear planning issues and emails a manager, organizations should define success criteria, use test accounts and controlled recipients, route provider calls through WorkOS Airlock with policy enforcement, and keep direct credentials inaccessible to the agent. The evaluation should cover successful routine emails, blocked attempts to send prohibited financial information, and approval requirements for unfamiliar distribution lists, while confirming actual delivery in Gmail rather than relying only on authorization logs. Testing should also verify that pending or rejected approvals do not permit sends and that approvals cannot be reused for modified requests. Teams should compare total human review, correction, recovery, setup, model, and service costs against manual completion time, tracking both active effort and elapsed approval delays. Expansion is appropriate only when routine work is accurate, policy violations are reliably stopped, approvals work as intended, and the remaining oversight effort produces worthwhile savings.

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