Should your AI provider have SOC 2 and ISO 27001 for the product tier you use?

Why the product tier matters when checking AI vendor certificates

When a professional services firm asks whether an AI provider holds SOC 2 Type II or ISO 27001 certification, the useful question is narrower: does that evidence cover the specific product, workspace, region, sub-processors and data flow your firm will actually use?

A certificate at company level can be helpful, but it is not enough on its own. Many AI vendors offer consumer, team, enterprise and API tiers with different retention settings, training exclusions, admin controls, logging, support terms and contractual commitments. The risk sits in the tier and configuration, not the brand name on the home page.

The practical answer for firms using AI with client data

Yes, ask for SOC 2 Type II and ISO 27001 evidence where the AI tool will touch client, matter, audit, valuation, financial or advisory data. Then check the scope. The report or certificate should map to the service you are buying, the hosting environment, the relevant security controls and the period you will rely on.

If the vendor cannot show whether the product tier is covered, treat the tool as unapproved for client confidential work until the gap is resolved. That does not mean the tool can never be used. It means your firm should limit it to low-risk, non-confidential tasks or use a controlled alternative with stronger evidence.

Check your AI vendor risk controls

What evidence to request before approval

Ask for the current SOC 2 Type II report, ISO 27001 certificate, statement of applicability where available, sub-processor list, data processing terms, data residency details and product security documentation. For regulated or client-facing work, also ask how prompts, outputs, uploaded files and logs are retained, deleted, accessed and excluded from model training.

The review should be recorded in a simple vendor decision file: who reviewed the evidence, which product tier was assessed, what data categories are permitted, what residual risks remain, and who approved use. This gives the firm an audit trail if a client, insurer, regulator or internal risk committee asks how the decision was made.

Red flags that should stop client-data use

Pause approval if the certificate does not name the relevant service, the SOC 2 report is unavailable under NDA, the retention terms are unclear, the vendor reserves broad rights to use customer content, the sub-processor list is missing, or admin controls such as SSO, role-based permissions and audit logs are only available on a higher tier than the one being purchased.

Another common issue is relying on a procurement screenshot instead of a contract. If the no-training promise, deletion commitment or data location control is only in marketing copy, capture it as an open risk and ask for contractual wording before the tool handles client work.

How to turn certification checks into an operating control

Make certification review part of an AI approval gate rather than a one-off legal question. Keep a register of approved tools, permitted use cases, data restrictions, evidence expiry dates and responsible owners. Re-check the evidence when the vendor changes product tiers, adds a new model provider, changes sub-processors or introduces a feature that processes data differently.

Maintain an AI governance evidence trail

For law firms, accountants, insurers and financial services teams, this matters because confidentiality, data protection, professional accountability and quality review do not disappear when a vendor has a security badge. The badge is one piece of assurance. The operating model is what proves control.

Conclusion

Do not approve an AI provider for client data on certification labels alone. Approve it when the certification scope, contract, data controls, admin settings, review process and audit trail all line up with the work your firm wants the tool to perform.

Put vendor controls into implementation