AI Governance Program Build
Five-Pillar AI Governance — Policy, Risk Management, Governance Operations, Third-Party AI Security, and Responsible AI
AI adoption is outpacing AI governance in most organizations. Teams are deploying models, integrating third-party AI services, and building agents without formal risk assessment, policy guardrails, or oversight structures. Shadow AI — unauthorized use of AI tools with corporate data — is the most immediate risk most organizations face.
This engagement builds a comprehensive AI governance program across five pillars: Policy & Standards (acceptable use, data handling, model development), Risk Management (use-case intake, model risk scoring, risk treatment), Governance Operations (committee model, decision workflows, shadow AI discovery), Third-Party AI Security (vendor assessment, data sharing controls, contractual requirements), and Ethics & Responsible AI (bias monitoring, transparency, human oversight).
The program is built through 5-8 stakeholder interviews, produces 5-8 policy documents, and maps to EU AI Act, NIST AI RMF, and ISO 42001 requirements. The result is an operational governance program — not a policy library that sits on a shelf.
Who This Is For
Ideal clients for this engagement.
The Problem
What this engagement addresses.
Shadow AI Proliferation
Employees across the organization are using AI tools — ChatGPT, Copilot, Midjourney, custom GPTs — with corporate data. Without discovery, policy, and guardrails, sensitive data leaks to third-party AI providers without any risk assessment or data handling controls.
No Use-Case Intake Process
AI projects launch without security review, risk assessment, or governance approval. By the time security is involved, the model is in production, the data pipeline is built, and remediation is costly. Governance must be integrated into the workflow, not applied after the fact.
Regulatory Uncertainty
EU AI Act, NIST AI RMF, ISO 42001, and industry-specific regulations create a fragmented compliance landscape. Organizations need a unified governance framework that maps to multiple regulatory requirements without duplicating effort.
Third-Party AI Risk
Organizations integrate AI services from multiple vendors without assessing model security, data handling practices, or contractual protections. Third-party AI introduces model risk, data risk, and supply chain risk that traditional vendor assessment processes do not cover.
Ethics and Responsible AI as Afterthought
Bias monitoring, transparency, and human oversight are treated as nice-to-have features rather than governance requirements. Responsible AI must be built into the governance framework from the start — not bolted on after a public incident.
Deliverables
What you receive.
AI Acceptable Use Policy
Organization-wide policy covering authorized AI tools, permitted use cases, data handling requirements, prohibited activities, and shadow AI reporting obligations. Includes role-specific guidance for developers, data scientists, and business users.
AI Risk Management Framework
Use-case intake workflow, model risk scoring methodology, risk treatment procedures, and exception management process. Risk scoring considers data sensitivity, autonomy level, regulatory exposure, and business impact.
Governance Operations Model
AI governance committee charter, membership, decision authority, and meeting cadence. Shadow AI discovery methodology and tooling recommendations. Use-case registry and approval workflows.
Third-Party AI Security Framework
Vendor assessment questionnaire for AI service providers, data sharing and processing controls, contractual security requirements, and ongoing monitoring criteria. Tiered assessment based on data sensitivity and integration depth.
Responsible AI Standards
Bias monitoring requirements, transparency and explainability standards, human oversight design patterns, and incident response procedures for AI-specific incidents (hallucination, bias, data leakage).
Regulatory Mapping
Control mapping across EU AI Act, NIST AI RMF, and ISO 42001. Gap analysis against current practices and remediation roadmap for compliance alignment.
Methodology
How the engagement works.
Discovery & Assessment
Weeks 1 – 2
- 5-8 stakeholder interviews (security, legal, engineering, data science, product, compliance)
- Current AI usage inventory and shadow AI discovery
- Existing policy and governance gap analysis
- Regulatory requirement mapping (EU AI Act, NIST AI RMF, ISO 42001)
Policy & Framework Development
Weeks 2 – 4
- AI acceptable use policy development
- Risk management framework and model risk scoring
- Governance operations model design
- Third-party AI security framework
- Responsible AI standards
Review, Approval & Launch
Weeks 5 – 6
- Stakeholder review of all policy documents
- Governance committee establishment support
- Use-case intake workflow implementation guidance
- Knowledge transfer and program launch support
Engagement Tiers
Scoped to your architecture.
Foundation
Core governance — AI acceptable use policy, risk management framework, and governance operations model. For organizations establishing baseline AI governance.
- AI acceptable use policy
- AI risk management framework with model risk scoring
- Governance operations model and committee charter
- Shadow AI discovery methodology
Standard
Complete five-pillar governance program with third-party AI security and responsible AI standards. For organizations with significant AI adoption and regulatory exposure.
- Everything in Foundation
- Third-party AI security framework
- Responsible AI standards
- Regulatory mapping (EU AI Act, NIST AI RMF, ISO 42001)
Enterprise
Multi-business-unit program with extended stakeholder engagement, custom regulatory mapping, and governance launch facilitation. For large organizations with complex AI ecosystems.
- Everything in Standard
- Extended stakeholder engagement (8+ interviews)
- Custom regulatory mapping (industry-specific requirements)
- Governance committee launch facilitation (first 2 meetings)
Prerequisites
- Executive sponsorship for AI governance program
- Stakeholder availability for interviews (security, legal, engineering, data science, product, compliance)
- Inventory of known AI tools and services in use (even partial)
- Regulatory requirements applicable to the organization (jurisdiction, industry)
Frequently Asked Questions
Common questions.
What if we do not know what AI tools our employees are using?
That is shadow AI — and it is the starting point for most organizations. The engagement includes shadow AI discovery methodology: network traffic analysis recommendations, SaaS management platform queries, procurement and expense data review, and employee survey approaches. You do not need a complete inventory to start governance; governance helps you build the inventory.
How does this map to the EU AI Act?
The regulatory mapping deliverable maps every governance control to EU AI Act requirements, including risk classification methodology aligned to the Act's risk tiers, documentation requirements, transparency obligations, and high-risk AI system requirements. The framework is designed to satisfy EU AI Act compliance as part of normal governance operations, not as a separate compliance exercise.
Do we need both this and Secure AI Architecture?
This engagement builds the governance program — policies, risk management, oversight structures, and third-party assessment. Secure AI Architecture builds the technical controls — reference architectures, threat models, guardrail specifications, and adversarial testing frameworks. They are complementary: governance without technical controls is unenforceable, and technical controls without governance are ungoverned.
Related Offerings
Often paired with this engagement.
Secure AI Architecture
Technical complement — secure reference architectures, AI threat modeling, and runtime guardrail specifications for the AI systems governed by this program.
LLM Application Security Assessment
Adversarial testing of LLM-powered applications — validates that governance controls are effective at the application level.
Security Program Strategy
Position AI governance within a broader multi-year security strategy that covers all security domains.
vCISO Advisory Retainer
Ongoing strategic security leadership that includes AI governance oversight as part of the broader security program.
Ready to discuss this engagement?
30-minute discovery call. We will discuss your application architecture, your specific concerns, and whether this assessment is the right fit.