AI Governance & Framework Services
The AI Governance Program That Holds Up When Auditors Ask For Evidence
An assessment tells you where you stand. This engagement builds the operating model you stand on. Ten signed policies. Seven defined roles. Every control maps to the article an auditor cites, across GDPR, NIS2, DORA, the EU AI Act, and HIPAA. Retention schedules and evidence trails are included.
Who Owns The Risk When The Agent Goes Off Script?
AI adoption is moving faster than the rules around it. Only 38% of organizations have a formal, comprehensive AI policy. The pressure to have one is coming from four directions at once.
of organizations faced a compliance consequence from an AI governance gap last year.
Regulators.
The EU AI Act, US state AI laws, and sector regulators now write obligations specific to AI.
Customers.
Security questionnaires now ask about your AI use, your vendors' AI use, and model provenance.
Boards.
Directors want a position on AI risk they can defend, with a named owner behind it.
Shadow AI.
65% of organizations discovered unsanctioned AI in use in the past 12 months.
Built On The PurpleSec® AI Security Readiness Framework
Inspired by NIST AI RMF and the MIT AI Risk Repository. Written to turn governance requirements into controls that operate in real environments.
One Risk Structure
A common way to identify and categorize AI risk across every team that touches AI.
Domains Tied To Controls
Each governance domain maps to a measurable outcome and a control you can enforce.
Continuous Oversight
Oversight of AI behavior in production, beyond a one-time review before deployment.
Audit-Ready Evidence
Records that answer an audit, an assessment, or a regulatory inquiry on request.
A Policy nobody Enforces Is The Same As No Policy
That is where most organizations sit today. The work below closes that gap, then keeps it closed as new AI tools and regulations arrive.
Get ready
- Inventory every AI system in use, sanctioned and shadow.
- Set your AI risk tolerance and an acceptable-use policy leadership signs.
- Name an owner for every AI decision, from model approval to incident response.
- Map each control to NIST AI RMF, ISO/IEC 42001, and your industry regulations.
Stay ahead
- Track new AI regulation and guidance, and update the control map when it changes.
- Review policy each time a new AI tool, model, or agent enters the business.
- Report AI posture to the board on a set cadence.
- Keep evidence current for the next audit, renewal, or customer questionnaire.
Map The Control Once And Answer Every Auditor Request
ISO/IEC 42001 is the certifiable core. NIST AI RMF gives the board a shared language. The security and privacy frameworks you already report against inherit the same control rows.
One control set
- ✓ Policies leadership signs
- ✓ An owner for every AI decision
- ✓ Controls mapped once
- ✓ Evidence kept current
AI governance & risk
- NIST AI RMF
- ISO/IEC 42001
- ISO/IEC 23894
- EU AI Act
- MIT AI Risk Repository
AI security
- OWASP Top 10 for LLM Applications
- OWASP Top 10 for Agentic Applications 2026
- MITRE ATLAS
Security & privacy overlay
- NIST CSF 2.0
- ISO 27001
- SOC 2
- GDPR
- HIPAA
Frequently Asked Questions
What Is AI Governance?
AI governance is the set of policies, roles, and controls that decide how an organization builds, buys, and uses AI. It also covers the evidence that proves those rules are followed.
A working program answers three questions. Who may use AI, and for what. Who owns the risk. How you know the rules held.
Which AI Governance Framework Should We Start With?
Most programs anchor on NIST AI RMF and ISO/IEC 42001. NIST AI RMF is voluntary and gives leadership a shared vocabulary: Govern, Map, Measure, Manage. ISO/IEC 42001 is a certifiable management system standard.
The PurpleSec® AI Security Readiness Framework maps to both, then turns them into controls you can enforce.
We Only Use Third-Party AI Tools. Do We Still Need Governance?
Yes. Most AI risk enters through tools you buy: enterprise assistants, AI features inside SaaS platforms, and model APIs.
Regulators and customers hold you accountable for how your data moves through those tools, whoever built the model.
How Is AI Governance Different From An AI Risk Assessment?
An assessment tells you where you stand. Governance builds the operating model you stand on. Many teams run the AI Risk Assessment first and use its scored risk register as the starting point for governance.
How Do We Stay Ahead As AI Regulation Changes?
Treat governance as a cycle. When a regulator publishes new guidance or a new AI tool enters the business, the control map and policies update with it. The AI vCISO service owns that cycle for teams without a dedicated AI governance lead.