guide · Evidence checked 2026-09-02

Govern the draft before the prompt

A practical, evidence-led decision guide. Product capabilities and limits are separated from anything that would require hands-on testing.

An AI writing trial often begins with the most sensitive material: an unreleased campaign, customer interview or internal strategy. That is backwards. The safe first step is to classify the content and establish what the product and its model providers may retain, reuse and expose.

The six questions that change approval

ControlEvidence to obtainFailure condition
Training usePlan-specific statement and contractOpt-out is assumed from a marketing headline
RetentionInput, output, logs and backup periods“Not used for training” is treated as “not stored”
Model routingCurrent subprocessors and regionsSensitive text can reach an unapproved provider
AccessRoles, SSO, sharing and audit eventsA public link or departed user retains access
DeletionUser, admin and contractual deletion pathNo testable removal workflow exists
Source truthOwner, approved corpus and review ruleFluent output can introduce unsupported facts

Start with synthetic documents. Then use one low-sensitivity real workflow and test access removal, export and deletion. Capture evidence for the exact plan: DeepL Write distinguishes free and Pro handling; Typeface is a contract-led enterprise decision; Lex and HyperWrite require their own review. One vendor's promise never transfers to another.

Procurement passes only when the team can name the data owner, allowed content classes, model route, retention period, deletion evidence and accountable human approver. A lower subscription price cannot compensate for an unbounded data path.

Primary action: build a one-page data-flow record before enabling real documents, then attach the current privacy notice, DPA and order-form exceptions to the approval.

Primary sources for verification