A practical checklist for boards, legal teams, deal teams, and committees evaluating private AI for sensitive shared work.
For teams that need a concrete evaluation checklist before bringing sensitive records into any AI workspace.
Primary search phrase: AI security checklist for sensitive documents. Related searches include private AI checklist, AI vendor security questions, confidential AI evaluation.
Before evaluating any AI vendor, list the records the group wants to use: board packs, minutes, diligence files, legal opinions, contracts, advisor notes, policies, or meeting records. Then classify what would happen if those records left the intended boundary.
This exercise quickly separates generic AI productivity from sensitive group work. If the documents are privileged, regulated, market-sensitive, or deeply private, the workspace needs stronger controls than an ordinary assistant.
Ask where documents, prompts, retrieved context, embeddings, outputs, logs, analytics, backups, and exports live. Ask where model inference runs. Ask whether data is used for training. Ask who can access customer data operationally and how that access is logged.
Ask how the product handles outside advisors, director access, matter scoping, and export at termination. Ask for a live demo on fictional data so the team can inspect product controls before sharing sensitive material.
Good answers are specific. They name systems, locations, sub-processors, access paths, retention, export formats, and limitations. Vague answers such as 'enterprise grade security' or 'we use encryption' are not enough for sensitive group work.
The final question is practical: after hearing the answers, would the board, general counsel, or investment committee be comfortable explaining the decision later. If not, keep asking.
| Criterion | Conventional pattern | Steward pattern |
|---|---|---|
| Weak answer | We are secure and enterprise-ready. | Documents, prompts, context, outputs, logs, and model path are described separately. |
| Weak answer | Your data is encrypted. | Encryption, residency, operator access, and key custody are treated as distinct claims. |
| Weak answer | We can show you after procurement starts. | A live demo on fictional records is available before a formal sales process. |
Ask where the full data path runs: documents, prompts, retrieval context, model inference, outputs, logs, analytics, backups, and export.
No. Encryption is important, but buyers also need residency, inference boundaries, operator access controls, logging, export, and training commitments.
A demo helps the team inspect whether the product actually matches sensitive group workflows before investing time in a formal process.
The live demo uses fictional records, so your team can inspect Steward's graph, vault, House Rules, citations, and team memory before sharing sensitive material or starting procurement.