The TPRM Response Playbook for AI Vendors

A repeatable process for answering third-party risk questionnaires when the third party is an AI vendor.

AI vendor risk questionnaires are becoming a routine, recurring cost of doing business, not a one-time hurdle. Handling them one at a time, from scratch, wastes time and produces inconsistent answers across vendors. This playbook gives you the structure to standardize the process.

Why AI Vendor TPRM Is Different

Traditional vendor risk questionnaires weren't built for AI-specific questions: model training data provenance, prompt retention, whether customer data trains the vendor's models, human review of outputs. A generic TPRM process misses these unless it's adapted.

The Standard Question Categories

  1. Data handling: What data the tool touches, where it's stored, retention period, and whether it is used for model training.
  2. Access and output controls: Who can see outputs, whether outputs are logged, and human review requirements.
  3. Sub-processors: Whether the vendor relies on other AI providers, and what is disclosed about that chain.
  4. Compliance posture: Relevant certifications (SOC 2, ISO 27001, ISO 42001), and regulatory alignment where relevant (GDPR, EU AI Act).
  5. Termination and data deletion: What happens to data and derived outputs when the relationship ends.

Building Your Response Library

Maintain a standing library of pre-approved language for each category above, reviewed and updated quarterly, instead of answering every questionnaire from scratch.

Escalation Triggers

Define in advance which answers require legal or security review rather than a direct answer from the library. For example: any vendor that can't confirm data isn't used for model training, or that discloses an undisclosed sub-processor chain.

This playbook gives you the categories and structure. Building your actual response library and setting your organization's specific risk thresholds is where this becomes real. That's the part we help with directly.

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