An AI Privacy Impact Assessment that maps the real data flow, not just the idea

It is often worth doing when an AI tool is being introduced into a workflow that involves personal information, sensitive information, automated outputs or meaningful third-party access. Common examples include customer-facing AI features, internal tools using employee or client data, model training or fine-tuning activities, and systems that generate outputs affecting people. A written assessment can help your team record the data flow, identify pressure points early and decide what follow-on work may be needed. It is a practical governance document, not just a formality for filing away.

An AI PIA usually looks at what personal information is involved, where it comes from, how it enters the system, how it is processed, what outputs are produced, who can access those outputs, and whether any third-party providers are involved. It may also consider retention, transparency, human review, internal access controls and whether the proposed use matches existing privacy wording or customer-facing documents. A useful version should be based on your real data practices, not just a generic list of privacy clauses, so the assessment needs to reflect the real workflow rather than a high-level product description.

We will usually need a clear explanation of the AI product, feature or workflow, the categories of data involved, where that data comes from, what the system is meant to do, who can access it, and whether external vendors or infrastructure providers are involved. Existing privacy policies, internal policies, diagrams, product notes, vendor terms and technical summaries can also be helpful. If the project is still evolving, we can assess the current model, but the document may need updating later if the data use or system design changes materially.

A template can help with structure, but AI projects often raise fact-specific issues that standard forms do not capture well. For example, the privacy analysis may change depending on whether prompts are stored, whether outputs contain personal information, whether customer data is used for training, or whether a third-party model provider has access behind the scenes. If the assessment does not match the actual system, it may be less useful for internal decision-making, stakeholder review or later document updates. A tailored assessment is usually more valuable where the workflow is novel or high impact.

No. This service covers the assessment document and legal input on the findings, not the full implementation of every recommendation. If the PIA identifies follow-on work, that might include updating your privacy policy, customer terms, internal governance documents, vendor contracts or consent wording. Technical changes, security remediation, regulator engagement, dispute work and ongoing representation are outside this fixed-fee.

Scope note: requirements and stakeholder expectations can vary, and third-party decisions sit outside Sprintlaw's control.

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