AI product legal review

What the engagement delivers

We map data and content rights, vendor terms, user disclosures, output risks and human oversight. The assessment separates existing legal duties from non-binding guidance and emerging proposals.

1. Define the feature, intended use and release version covered.
2. Map inputs, provider interactions, stored information and outputs.
3. Compare the documented design with the proposed user terms and operational controls.
4. Prepare an issue register with decisions, owners and dependencies.

Keep the assessment tied to the actual product configuration. A change of model provider, input source or output use can change the questions even if the feature name stays the same.

For features that create or alter audio, images or video, examine the synthetic-information definition and exclusions in the February 2026 IT Rules amendment. MeitY’s explanatory FAQ distinguishes realistic synthetic media from specified routine editing and other excluded uses. Describe the actual output and publishing role before assessing the intermediary requirements; the label “AI-powered” does not settle that assessment.

Information to organise

• Feature specification
• model-provider terms
• data sources
• intended users
• output examples
• retention settings
• human review and complaint process.

Describe whether information is used only for inference or also for improvement or training, according to the relevant arrangements. Identify optional settings and contractual commitments separately from assumptions about provider behaviour. Use synthetic or redacted examples for initial discussion rather than sending customer documents.

A design or evidence issue to resolve

A summarisation feature using customer documents raises different questions from a public generator using licensed training material. Describe the actual data path and output use before adopting a standard disclaimer.

For example, a support assistant may draft replies for staff in one release and send them directly to customers in another. Record that change in the review brief, including who can intervene, how errors are reported and what the customer is told. The earlier human-review description should not remain in the terms after the workflow changes.

Boundaries and next steps

No general “AI compliant” badge is promised. Model evaluation, technical testing, intellectual-property opinions and regulated-sector advice are expressly scoped.

The written scope identifies products, entities, jurisdictions, deliverables and fees. Share an initial description rather than confidential source code or personal datasets through the public enquiry form.

The handover can include a data-and-content flow, vendor-term questions, proposed disclosure changes and an unresolved-decision log. It identifies where technical evidence or specialist advice is still needed. Product owners remain responsible for implementing and verifying the agreed behaviour rather than treating a written review as proof of implementation.