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AI Governance
AI Vendor and Model Assessment
Evaluate AI providers and models for data handling, training provenance, security, reliability, contract protections, and regulatory obligations.
What it covers
The engagement in detail
Evaluation of third-party artificial intelligence providers and the models they supply, covering training data provenance, data handling and retention commitments, model security, output reliability and evaluation practice, subprocessor chains, contractual protections, and the regulatory obligations the arrangement transfers or retains.
Who it is for
Designed for established organizations measuring and maturing an existing security program, and law firms, corporate legal departments, and the clients they advise.
What you receive
Deliverables from this engagement
- Vendor assessment reports
- Contractual gap analysis
- Risk determinations
Terms
How an engagement works
Every engagement is scoped individually and conducted under a nondisclosure agreement and a master services agreement, beginning with a scoping conversation and a written statement of work that defines scope, deliverables, and sequence. The four steps this practice follows are set out in full on the AI Governance page.
- Prepare for a transaction or assess a third party
- Establish governance and policy
- Established Enterprises
- Law Firms and Legal Departments
AI Governance
Other services in this practice
Govern the AI you build, buy, and use, against ISO 42001, the NIST AI Risk Management Framework, and emerging state law.
- AI Governance Program DevelopmentDesign an AI governance program on the NIST AI RMF and ISO/IEC 42001: decision rights, policy, use case intake, risk assessment, oversight, and monitoring.Governance
- AI Regulatory Readiness AssessmentGap assessment against the EU AI Act, the Colorado AI Act, the Texas Responsible AI Governance Act, and sector expectations for AI accountability.Regulatory
- AI System Inventory and Use Case Risk ClassificationDiscover and catalog the AI systems in use across your organization, whether built, bought, or embedded, and classify each use case by risk.Governance
- Shadow AI Discovery and GovernanceFind unsanctioned AI use, measure the data exposure it creates, and replace it with sanctioned tools, acceptable use standards, and technical controls.Governance
- AI Product Security and AssuranceAssess the AI features in your product for prompt injection, data leakage, output handling, access control, tenant isolation, and evaluation practice.Product security
- AI Risk Assessment and Ongoing MonitoringRecurring assessment of deployed AI systems for fairness, reliability, transparency, security, and regulatory fit, with the documentation regulators expect.Risk and maturity
Start with a confidential conversation
Thirty minutes on whether this is the right engagement for the question you have been asked, and what it would take to answer it.