AI vendor diligence: what to establish before a Japan proposal
Verify product limits, data handling, evaluation evidence and support responsibilities before making commitments.
An overseas AI vendor and its Japan partners need the same factual account of what the product can deliver. Otherwise a sales claim can become a prospect’s expectation that the implementation team cannot meet. Use the proposed application and contract to establish the limits before repeating the claim.
Check the product for the intended use
Identify the model and application versions, supported languages, required infrastructure and licence conditions. Ask for relevant tests and their limits, not an accuracy percentage without a dataset or task definition. Establish uses the vendor supports, excludes or has not evaluated. A missing capability may narrow the proposal; it should not be quietly presented as available.
Follow the information through every provider
Confirm prompts, retrieval, output, telemetry, logs, backups, subprocessors and support access. Record retention, secondary use, deletion and location conditions. Review the actual arrangement against the buyer’s privacy and contractual requirements. A domestic reseller or a self-hosted model does not by itself answer these questions.
Give partners claims they can substantiate
Prepare Japanese product descriptions and demonstrations with clear conditions. Distinguish vendor-reported results from independent findings and customer-specific tests. Record which support hours and response commitments are included in the proposed contract. Agree which Japanese sales materials, product training and technical support each local partner will receive, and name the teams responsible for providing them.
Agree who installs, supports and responds to incidents
Name the parties responsible for installation, permissions, output review, updates and incident response. Test who receives a report when the application discloses the wrong record or performs an incorrect action. Define what evidence must accompany an escalation. The operating plan should remain usable after the sales and launch teams move to their next project.
Make change and exit conditions explicit
Ask how the vendor communicates model changes, maintains supported versions and handles a rejected upgrade. Test export where supported and document any limits on data, prompts, adapters or configuration. Include termination and deletion conditions in the contract discussion. These questions help a buyer assess the proposed service; they do not amount to a guarantee that any AI product is safe for all uses.
// Key Takeaways
What to remember
- Use task-specific evidence and clearly stated product limits.
- Keep claims and contractual support consistent across vendor and channel.
- Assign incidents, changes and exit before customer handover.
// FAQ
Frequently asked questions
What makes an AI accuracy claim useful in procurement?
The task definition, dataset, scoring method, product version, test conditions and known failures. A percentage without that context does not establish suitability.
Should a buyer accept a Japanese reseller as proof that data stays in Japan?
No. Review the actual services, processing, access, logs, backups and support terms. The seller’s address alone does not establish the data flow.
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