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“Is the new AI tool a creep?” is best answered by tracing what it will see, what the provider will do with that information, and whether you can reduce and assess the risks before processing starts. The product and its terms matter: do not assume it uses client data for model training, or assume that it does not. If you cannot work out what happens to the data or control a material risk, pause adoption and choose a more assessable workflow or service.
What information will the AI feature receive and return?
Start with a data map for the actual website workflow, not a general description of the product. The Federal Trade Commission recommends tracking personal information through websites, service providers, storage locations, and access permissions. Map the information from the moment it is collected or entered to the point it is stored, accessed, or returned.
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Inventory the inputs and outputs
- List the pages, website content, user submissions, records, credentials, and logs the feature can receive. Include information passed automatically as well as information a person deliberately submits.
- Record what the feature generates or returns, and where that output goes next—for example, whether it is placed on a page or passed into another workflow.
- Identify personal or sensitive information in the material, including information that may appear in free-text submissions or logs rather than a named form field.
Trace storage and access
- Find out where the information is held, who can access it, and which vendors, service providers, or subcontractors may be involved.
- Check whether the feature receives live website data or only a deliberately selected sample, and document the path data takes in either case.
If you cannot describe the flow well enough to record it, you do not yet have a sound basis for approving the feature.
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For each input, ask whether the AI function needs it to perform the intended task. The FTC’s business security guidance recommends keeping only information needed for the business. Apply that principle before sending information to the feature, rather than relying on a later deletion request to undo unnecessary exposure.
- Remove fields, records, or page content that are not needed for the stated purpose.
- Where practical, test with a redacted sample or content that contains no live personal information.
- Avoid sending sensitive client or customer information unless there is a clear need and you have assessed the safeguards and applicable obligations.
- Note which data you chose to exclude and whether the feature still works as intended.
Minimization does not establish that a service is otherwise suitable; it narrows what the service receives and should be considered alongside the provider’s terms and the workflow’s risks.
What does the provider say it will do with the information?
Read the contract, privacy terms, and technical documentation for each processing purpose. Ask directly: “Will the vendor use my client’s information to improve its models?” Also establish what the provider says about service delivery, retention, product improvement, and model development. These are questions to verify for the specific service and plan, not assumptions to make about AI vendors generally.
- What information is retained, for what purpose, and under what deletion terms?
- Can the provider use submitted information for a purpose beyond delivering the feature?
- Which parties can access the information, and what service providers or subcontractors are involved?
- What security documentation and contract terms apply to the particular workflow?
- Can you limit or disable processing, and can you change providers if the terms or risk become unacceptable?
Compare candidate tools using the same questions: data requirements; purposes and reuse; retention and deletion; access and subcontracting; security documentation; contractual roles; visibility into assessments; processing controls; and the ability to switch. A feature that cannot be assessed is not made acceptable merely by having a familiar interface.
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Who decides the purpose and means of each processing activity?
Do not assume that a provider has the same data-protection role for every activity. The Information Commissioner’s Office (ICO) gives examples distinguishing processing a provider performs on a client’s instructions—such as prediction for a client—from the provider’s own model development and training. Check the contract and documentation against what actually happens in your workflow, activity by activity.
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Record which party decides why and how each operation takes place, what instructions govern it, and whether the written terms match the real data flow. If the roles or responsibilities are unclear, resolve that before the feature handles personal information.
Have you assessed the privacy risk before processing begins?
Assess the specific feature, information, affected people, and context before turning it on. ICO guidance says AI processing will, in the vast majority of cases, involve processing likely to be high risk, while still calling for a case-by-case assessment. Document why this particular use is or is not high risk, what safeguards you will use, who owns the decision, and what risk remains.
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Where a data protection impact assessment (DPIA) is required, complete it before processing starts. The ICO’s accountability and governance page, last updated 15 March 2023, says: “You should not see DPIAs as simply a box ticking compliance exercise.” That page’s update date is not a statement that it captures every later legal change; the ICO says its guidance is under review following changes made by the Data (Use and Access) Act.
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Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Do location or transparency obligations affect the workflow?
Identify where your business, client, provider, and affected people are located, and which rules apply to the particular feature and use. The ICO material is UK data-protection guidance; the FTC material is US business guidance. Neither should be treated as a worldwide rulebook.
For one specific EU requirement, the European Commission published guidelines on AI Act Article 50 transparency obligations on 20 July 2026 and says those obligations apply from 2 August 2026. This is not a blanket effective date for all AI or privacy rules. Check whether Article 50 applies to the feature and use at hand rather than assuming that any AI use triggers the same notice.
What should make you pause, and how will you review the decision?
Set the adoption conditions before enabling the feature. Keep a record of the data map, the provider’s stated purposes and terms, the role analysis, the risk assessment, safeguards, and the person responsible for approving and revisiting the use.
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- Pause if you cannot establish what data is sent, where it goes, who can access it, or what the provider does with it.
- Reduce or redesign the workflow if the feature receives information it does not need or if a safer sample-based process can meet the same purpose.
- Do not proceed where required assessment is incomplete or material residual risk cannot be reduced as required for the deployment.
- Set a review trigger for changes to terms, model, feature, retention, or subcontractors, and define who can disable the feature or move the work elsewhere.
Keep the review live rather than treating approval as permanent. The ICO’s procurement guidance calls for due diligence and review as a system or its use changes. Its accountability guidance also warns against bringing a data protection officer into the decision only at the last minute: “Data protection should not be an afterthought, and a DPO’s professional opinion should not come as a surprise at the eleventh hour.”
If you can map the data, limit it to what is needed, verify the provider’s purposes and roles, and assess and control the relevant risks, you have a basis for a documented decision. If you cannot assess the processing or reduce a material risk, do not put the tool into the client website workflow until you can—or use a different solution.
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