Use this playbook to scope a document AI pilot that creates a real evaluation signal: fast time-to-value, clear controls, and measurable operational lift.
Summary
A successful pilot proves one controlled workflow can produce cited, reviewable answers fast enough to matter operationally without creating governance debt.
Sections
3
Questions Covered
3
Executive Summary
The right pilot is narrow, evidence-driven, and ends with production-readiness decisions rather than a one-off novelty demo.
Section 1
Do not begin with a sprawling multi-team pilot. Pick a single collection, such as policies, contracts, or due diligence materials, and a single review motion that currently consumes measurable analyst time. That gives you a clean baseline and a clear success criterion.
Section 2
Before launch, decide how answers will be judged. For most teams this means requiring citations, preserving the source context, and logging queries and outputs. That lets you measure not just speed but whether the system is safe to operationalize.
Section 3
A good pilot ends with decisions about access controls, retention, monitoring, and integration paths. If the pilot only shows that a model can answer a few questions, it has not reduced implementation risk.
Security, legal, operations, and platform teams evaluating governed document intelligence should use this playbook to keep the pilot measurable and production-relevant.
Choose one document set, define the review motion, set evidence expectations, then measure value against a baseline before expanding scope.
Trying to prove too many workflows at once usually produces noisy evaluation data and makes it hard to separate model value from operational confusion.
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