Diligence covers where data is stored and processed, whether inputs are used for training, retention periods, subprocessors and which underlying models are used, security certifications, tenant isolation, accuracy validation, and contractual terms including confidentiality and indemnification.
For legal buyers it also covers whether the vendor's terms permit the confidentiality commitments the firm owes its own clients.
Alternative Names:
AI Vendor Assessment, Legal AI Procurement Diligence
Why it Matters?
A firm cannot promise a client stronger protection than its vendor contractually provides, so diligence is what makes client-facing confidentiality representations accurate. The questions that most often surface problems are training on inputs, subprocessor disclosure, and retention defaults, because those are frequently buried in terms of service rather than negotiated.
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Frequently asked questions
What are the essential AI vendor diligence questions?
Do security certifications cover AI-specific risks?
