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Before sending business or personal information to an AI service, verify four things in the signed agreement, data-processing addendum (DPA), service terms and product settings: what data the vendor receives, exactly why it may process that data, how long each copy is retained, and which companies or models can access it. Treat model training, evaluation, benchmarking, human review, safety monitoring, analytics and product improvement as separate permissions—not as questions answered by a general “business data” or “no training” statement.
The contract should identify the parties’ roles, define prompts, files, outputs, feedback, telemetry and derived data, and set enforceable limits on reuse. It should also provide a deletion and return process, subprocessor notice and objection rights, security and incident assistance, audit evidence, and remedies. The Information Commissioner’s Office (ICO) AI contract guidance is a useful UK GDPR baseline; voluntary EU model AI clauses can help public-sector buyers structure negotiations, but they are not a complete agreement or a substitute for data-protection obligations.
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Why ordinary privacy wording is not enough
AI products generate and copy information across several systems: the model endpoint, abuse and safety filters, logs, support tools, analytics, backups and sometimes an upstream model provider. A privacy notice may describe these activities at a high level, while the operative contract grants different rights for different services. A statement that a vendor “does not train on customer data” may cover one product but not feedback, files, metadata, human review, evaluation datasets or a separately enabled model.
Review the complete data path and the documents that govern it. The contract must bind the named service, add-ons, regions, models and tenant settings you will actually use. If a feature routes requests to another provider, the terms for that route matter as much as the headline vendor agreement.
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Assemble the documents and map the real service
Collect the master services agreement, DPA, security addendum, service-specific terms, acceptable-use rules, product documentation, subprocessor list and order form. Record the exact product edition, model names, region, retention controls and whether an administrator has enabled optional data-sharing or feedback features.
Draw a simple flow for each use case: who submits the prompt; what files or connected applications are attached; which model receives it; where logs and backups are stored; which subprocessors handle support, safety or hosting; and what remains after deletion. Do this separately for development, testing and production. The same vendor can apply different terms to an API, a consumer interface and an enterprise workspace.
Step-by-step contract review
1. Define every data category
Do not rely on a single definition of “customer data.” Ask the contract to distinguish:
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- Prompts, uploaded files, images, audio, code and retrieved documents.
- Generated outputs and conversation history.
- Feedback, ratings, support tickets and content submitted for troubleshooting.
- Usage data, telemetry, device identifiers, IP addresses and account metadata.
- Derived, deidentified, anonymized and aggregated information, including embeddings, summaries and evaluation records.
- Information supplied by employees, customers, contractors and connected applications.
Check whether each category is covered by confidentiality, deletion, access restrictions and reuse limits. “Personal data” may omit commercially sensitive information, while “content” may be broad enough to include it. Definitions should apply to every selected model and add-on.
2. Assign roles, purposes and instructions
For each processing activity, identify whether the customer or vendor is controller, processor or another legally relevant role. State who determines the purpose and essential means, which documented instructions apply, the data subjects and categories involved, the processing duration and each party’s legal duties.
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Require the vendor to tell you if it cannot follow an instruction or believes an instruction breaches data-protection law. The ICO recommends detailed processing information and instructions in the contract, not merely a link to changing online terms. Make responsibilities clear for data-subject requests, impact assessments, cross-border transfers and breach notifications.
3. Negotiate data reuse as separate permissions
Create a schedule that answers “may the vendor use this data for this purpose?” for every category. Address, separately:
- Training or fine-tuning the vendor’s general models.
- Evaluating models, creating benchmarks or testing safety.
- Human review, quality assurance and abuse investigations.
- Analytics, diagnostics and product improvement.
- Service-specific model customization for your tenant.
- Sharing with affiliates, subprocessors or upstream model providers.
State whether each use is prohibited, allowed only on written instructions, or optional through a contractual opt-in or product setting. Identify whether a setting is merely a technical control or an enforceable promise. Restrictions should bind affiliates and subprocessors and should survive termination for data that has not been deleted.
An example February 2024 OpenAI DPA permits processing needed to provide and support services, including analytics and safety monitoring, and permits certain deidentified, anonymized or aggregated information to improve systems and services. That is an example of why you must read the applicable service terms rather than generalize from a vendor slogan or from another product.
4. Examine deidentification and derived data
Ask how deidentification is performed, who decides that the standard is met, whether reidentification or linkage is possible, and whether the vendor can combine the result with other data. Define whether embeddings, labels, summaries, prompts stripped of names, or aggregate statistics remain subject to your restrictions.
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The cited February 2024 OpenAI DPA allows continued improvement use of information derived from customer data when it has been deidentified, anonymized or aggregated so it is no longer personal data and does not identify the individual or customer. If your risk tolerance is lower, negotiate a ban on general model improvement even after deidentification, or require a documented standard and approval process.
5. Make retention and deletion measurable
Request a retention matrix by product, data type and operational purpose. It should state:
- Default and maximum live-system retention.
- Log, safety-review and support-ticket retention.
- Backup expiry and disaster-recovery copies.
- Legal holds and other statutory exceptions.
- Return format and timing at termination.
- Deletion deadlines for the vendor and each subprocessor.
- How you receive deletion confirmation or an exception report.
The ICO says contracts should instruct processors to delete or return personal information at the end of the contract unless law requires storage. The February 2024 OpenAI DPA describes a maximum 30-day retention period for API Service Customer Data, subject to a legal-retention exception. Its ChatGPT Enterprise Service Customer Data provision instead retains data during the agreement term unless otherwise stated. These are product-specific contractual examples, not universal AI-vendor defaults.
6. Map subprocessors and upstream providers
Obtain the current list of subprocessors, their locations, functions and access to content. Check how much advance notice you receive of changes, how objections work, what cure or termination rights apply, and whether the vendor remains responsible for subcontractor conduct.
In the February 2024 OpenAI DPA example, customers who subscribe to notifications receive at least 15 days’ notice before certain subprocessor-list changes take effect, with an objection process described in that DPA. The same document states that OpenAI remains liable for its subprocessors subject to the agreement’s liability limits. Do not assume another vendor offers the same notice or responsibility allocation.
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7. Specify security and incident assistance
Attach or incorporate technical and organizational measures rather than accepting “industry standard security.” Check for encryption in transit and at rest, least-privilege access, tenant separation, key management, vulnerability handling, resilience, backups, restoration testing, logging and personnel confidentiality.
Set an incident-notification clock, required contents, communication channels and cooperation duties. The vendor should help you investigate, contain and remediate an incident and meet applicable breach deadlines. It should also assist with data-subject requests, data-protection impact assessments and regulator inquiries. Confirm whether safety or abuse teams can access content and under what controls.
8. Secure audit and assurance evidence
Determine whether you can conduct a direct audit, rely on independent reports, or use a combination. Negotiate frequency, notice, scope, confidentiality, assessor qualifications, cost allocation and remediation deadlines. Ask for current SOC, ISO or equivalent reports, penetration-test summaries and exception statements where available.
Vendor agreements often limit direct audits and substitute third-party certification summaries. The February 2024 OpenAI DPA example permits audit cooperation under stated conditions and says third-party audit or certification summaries may be provided where law permits. Read the conditions: a report that excludes the model or region you use may not be sufficient evidence.
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Record the exact model and routing configuration in the order form or an attached schedule. A model switch can change the provider, retention, location and applicable contract. Microsoft documentation describes Anthropic-model scenarios in which some models operate under Microsoft terms as subprocessors, while certain models with Data Retention require explicit enablement and Anthropic’s separate terms; those models are not subject to Microsoft’s Customer Agreement and DPA. Treat this as a configuration-specific example, not a general rule. Confirm which provider’s terms govern every model, feature, region and setting you enable.
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10. Plan exit, migration and legal holds
Define export formats, assistance during migration, disabling access, deletion of indexes and caches, backup expiry, and a written certificate or report. State what happens to data in safety systems, fraud records and legally required archives. Require the vendor to pass deletion instructions to subprocessors and to identify any copy it cannot remove immediately, the legal basis for keeping it and its final deletion date.
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Use the same data and deployment scenario when comparing vendors or negotiating alternatives. Record the answer in writing rather than scoring marketing claims.
| Review axis | Questions to answer | Evidence to request |
|---|---|---|
| Reuse | Can prompts, files, outputs, feedback or derived data be used for training, fine-tuning, evaluation, benchmarking or general improvement? | Clause numbers, opt-in records and screenshots of applicable settings |
| Retention | How long does each data type remain in live systems, logs, safety tools and backups? | Product-specific retention schedule and deletion report |
| Subprocessors | Who receives data, where, for what function, with what notice and objection rights? | Current list, change procedure and responsibility clause |
| Audit | Can you audit directly, or only review independent reports? What happens when evidence shows a gap? | Report scope, recency, exceptions and remediation commitments |
| Model and routing | Which provider’s terms apply to each model, region and optional feature? | Configuration record and incorporated provider terms |
| Remedies | What assistance, indemnity, service credits, termination or other remedies apply after a failure? | Liability, cooperation, cure and termination provisions |
Red flags that warrant a pause
- A “no training” promise appears only in marketing material or covers customer content but not feedback, metadata or derived data.
- The DPA incorporates web terms that the vendor can change without notice.
- Retention is described as “as long as necessary” with no maximum, backup rule or deletion confirmation.
- The subprocessor list omits locations, functions, upstream model providers or an objection remedy.
- The vendor can use deidentified data without defining the deidentification standard or reidentification controls.
- Audit rights exclude the service, region or model you use, and no equivalent assurance report is available.
- A model or feature is governed by separate provider terms that your procurement or privacy team has not reviewed.
Using regulatory templates without overrelying on them
The ICO’s AI “Contracts and third parties” guidance is written for a UK regulatory context and frames expectations under UK GDPR. It is a baseline for documenting roles, instructions, security, assistance, audits and end-of-contract deletion; it is not a vendor-specific safe harbor.
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The EU model contractual AI clauses were published as voluntary tools for public organizations procuring externally developed AI. The EU page says they should be customized, do not replace the GDPR or other applicable laws, and do not constitute a full contract. Use them to identify missing topics, then integrate the needed language into your DPA, security terms and commercial agreement.
A practical approval workflow
- Inventory the use case. List data subjects, sensitivity, jurisdictions, connected systems, expected volume and whether prompts contain regulated or confidential information.
- Freeze the configuration. Record product edition, model, region, retention settings, administrator controls and any feedback or data-sharing switches.
- Complete the clause matrix. Mark each reuse purpose, retention period, subprocessor, security control, audit right and remedy as allowed, prohibited or unresolved.
- Test operational promises. Ask the vendor to demonstrate deletion, export, access logging, setting changes and incident contacts in the exact tenant or API environment.
- Negotiate exceptions. Resolve legal holds, safety records, backups, deidentified data, upstream providers and model changes before launch.
- Obtain sign-off and monitor. Have privacy, security, procurement and the business owner approve the final data flow. Recheck terms, subprocessors and configuration whenever the service or model changes.
When specialist legal review is warranted
Obtain qualified counsel for regulated or sensitive information, children’s data, health or financial records, employment decisions, cross-border transfers, high-impact automated decisions, custom training, or a contract with unusual liability and audit limits. Counsel should review the actual agreement and data flow for the governing jurisdictions; neither an ICO checklist nor voluntary EU clauses determine compliance on their own.
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