AI Governance
Govern your Artificial Intelligence (AI) with the same rigor examiners expect everywhere else. We assess what you run today, uplift what is weak, and build the AI governance program your board, regulators, and auditors expect.
Our flagship offering
An AI governance program calibrated to how examiners think
Best for
- You are deploying or scaling AI, including generative AI, and the board or your regulators are asking how it is governed.
- AI is already in use, but inventory, risk tiering, model validation, or AI policies are missing, outdated, or inconsistent.
- You need to show alignment to recognized standards before an examination, audit, or third-party due diligence review.
What you receive
- A current-state assessment against the four National Institute of Standards and Technology (NIST) AI Risk Management Framework functions (Govern, Map, Measure, and Manage), spanning the full AI lifecycle from development through deployment and ongoing use.
- An AI system inventory with risk tiering, plus a governance documentation gap map: existing policies, standards, and procedures flagged current, outdated, missing, or inconsistent.
- An AI Management System blueprint aligned to ISO/IEC 42001, with impact assessment templates aligned to ISO/IEC 42005 and a European Union AI Act (EU AI Act) risk-tier mapping where in scope.
- A board-ready readout and an operator-ready 30, 60, 90 day roadmap.
Scope
Two tracks, sold separately
Engage one track or both, in parallel or in sequence, calibrated to where your AI program is today.
Track A: Governance and Oversight
- AI governance policy and operating model
- AI inventory and intake
- Risk tiering and appetite
- Oversight committee and roles across the three lines of defense
- Third-party AI oversight
- Impact assessments
- Regulatory mapping
- Issue management and board reporting
Track B: Technical and Model Risk
- Model development lifecycle and documentation
- Independent validation and testing
- Data governance and lineage
- Bias and fairness testing
- Performance monitoring and drift detection
- AI system security
- Human oversight controls
- Secure development practices
How the engagement runs
Three phases, scoped to your estate
Phase 1
AI Governance Assessment
Current-state baseline
Phase 2
Targeted Uplift
Scoped to priority gaps
Phase 3
Program Build-Out
Full operating model
Framework alignment
Anchored to the standards your reviewers recognize
NIST AI RMF and the Generative AI Profile
The National Institute of Standards and Technology framework for managing AI risk across the Govern, Map, Measure, and Manage functions, with a companion profile for generative AI.
ISO/IEC 42001
The international standard for an AI management system.
ISO/IEC 42005
The international standard for AI system impact assessment.
European Union AI Act (EU AI Act)
The European Union regulation that tiers AI systems by risk and sets obligations accordingly.
Frequently asked questions
AI governance, answered
What is an AI governance program?
An AI governance program is the set of policies, oversight roles, risk controls, and documentation that govern how an institution develops, deploys, and monitors Artificial Intelligence (AI). For regulated financial institutions, it establishes accountability across the three lines of defense, an AI inventory with risk tiering, model validation, and board reporting, aligned to recognized standards such as the National Institute of Standards and Technology (NIST) AI Risk Management Framework and ISO/IEC 42001.
Which standards does the AI Governance offering align to?
The offering aligns to the National Institute of Standards and Technology (NIST) AI Risk Management Framework and its Generative AI Profile, ISO/IEC 42001 for AI management systems, ISO/IEC 42005 for AI impact assessment, and the European Union AI Act (EU AI Act) where it is in scope.
What is the difference between Track A and Track B?
Track A, Governance and Oversight, covers the AI governance policy and operating model, AI inventory and intake, risk tiering and appetite, oversight committee and roles, third-party AI oversight, impact assessments, regulatory mapping, and board reporting. Track B, Technical and Model Risk, covers the model development lifecycle, independent validation and testing, data governance and lineage, bias and fairness testing, performance monitoring and drift detection, AI system security, and human oversight controls. The two tracks are sold separately and can run in parallel or in sequence.
Does the AI Governance offering cover generative AI?
Yes. The assessment spans the full AI lifecycle from development through deployment and ongoing use, including generative AI, and references the National Institute of Standards and Technology (NIST) Generative AI Profile alongside the core AI Risk Management Framework.
When should a bank or credit union start on AI governance?
The right time is when you are deploying or scaling AI and the board or your regulators are asking how it is governed, when AI is already in use but inventory, risk tiering, model validation, or AI policies are missing or inconsistent, or when you need to show alignment to recognized standards before an examination, audit, or third-party due diligence review.
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