Supply Chain draft

Request the AI feature inventory. For each AI-enabled SaaS tool in use, the inventory should name the model family and version where the vendor discloses it (e.g. GPT-4o behind a given Copilot capability, Claude 3.5 Sonnet behind a given assistant) and the legal entity operating the inference endpoint (OpenAI, Anthropic, the SaaS vendor's own model team, an Azure OpenAI deployment). An entry that lists only the SaaS vendor and a marketing name for the AI feature does not satisfy this criterion. Where the vendor refuses to disclose the model or provider, record that refusal explicitly so the gap is visible rather than hidden.

Review the AI-specific clauses in each SaaS contract. The clause should name a minimum notice period (typically 30 to 90 days) before any model swap, version upgrade, or change of the underlying model provider takes effect for the tenant. Acceptable evidence includes a contractual right to a written change notice describing what changes (model family, version, provider), a defined evaluation window during which the organisation can assess impact, and a documented escalation path. A general 'service may be updated from time to time' clause does not satisfy this criterion. Where the SaaS vendor refuses such terms, document the refusal and the residual risk rather than treating silence as agreement.

Applies only to SaaS tools where the customer's data is used to fine-tune or otherwise adapt a model (vendor-managed fine-tunes, customer-specific embeddings backed by a vendor model, retrieval-augmented configurations that produce a customer model artefact). For each such tool, the contract or vendor documentation should describe the base model's training-data provenance at a useful level of detail (publicly disclosed corpora, vendor-curated datasets, third-party licensed data) and the licensing terms attached to outputs derived from that base. A clause that names only the customer's own fine-tune contribution and is silent on the base model's training data does not satisfy this criterion. Tools that do not offer fine-tuning are out of scope for this criterion and should be marked not applicable.

Request the model card library. For each model behind an in-production AI feature (vendor-hosted SaaS model, self-hosted model, fine-tune of a base model), the record should cover: model identity and version, the legal entity producing the model, training-data categories at the level the provider discloses (e.g. publicly disclosed corpora, licensed datasets, vendor-curated data), declared intended use and out-of-scope use, known limitations and bias evaluations, and version history with the date of the most recent change. Acceptable formats include the original Hugging Face model card, the provider's published model documentation (OpenAI system card, Anthropic model card, Microsoft Responsible AI transparency note), or an internally maintained record where the provider does not publish one. A marketing page describing the AI feature does not satisfy this criterion. Records older than the current model version in production are out of date and should be flagged as such.