Executive briefing: AI governance
What Is AI Assurance? A Board Guide to Proving Your AI Can Be Trusted
AI assurance is the process of measuring, evaluating and communicating whether an AI system is trustworthy, as UK government guidance defines it. It turns claims about AI into evidence, through techniques such as risk and impact assessment, bias audit, compliance audit and conformity assessment. It can be done internally or by an independent third-party AI assurance provider.
Correct as of 28 September 2026. Regulation and guidance change. If you are reading this later, check for updates before relying on it.
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- A policy says what should happen. Assurance shows what does happen, with evidence someone else can rely on.
- UK government guidance names six assurance techniques, from risk assessment and bias audit to conformity assessment and formal verification.
- Third-party AI assurance adds independence. It does not replace internal assurance, and it can only test the evidence you already hold.
- ISO/IEC 42001 is the management system that produces that evidence. Assurance and certification test it.
- Start with an inventory, a named owner for each system and recorded risk assessments. Without them, there is nothing to assure.
Why the board should care
Claims become commitments
Telling a customer, insurer or regulator that your AI is accurate, fair or secure is a claim you may later have to prove. Assurance is how that claim becomes evidence.
Independent checks are becoming normal
The UK government has set out a roadmap to professionalise third-party AI assurance. Organisations that already hold the evidence will find independent review easier to pass.
Nothing to assure without the basics
An assessor can only test what you can show. With no inventory, owners or risk records, an external review mostly confirms the gap.
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FAQ
Frequently asked questions
What is AI assurance?
AI assurance is the process of measuring, evaluating and communicating whether an AI system is trustworthy. UK government guidance from DSIT describes it this way. In practice it means turning claims about AI, such as accuracy, fairness and security, into evidence that a customer, board or regulator can rely on.
What is an AI assurance framework?
UK government guidance describes an AI assurance toolkit made of assurance techniques, such as risk assessment, impact assessment, bias audit, compliance audit, conformity assessment and formal verification, together with technical standards such as ISO/IEC 42001. An organisation builds its own framework from these, in proportion to the risk of each AI system.
What is third-party AI assurance?
Third-party AI assurance is assurance carried out by an independent provider, rather than by the teams that build or use the AI. Its value is independence. It does not replace internal assurance: an assessor can only test the inventory, owners, risk assessments and records the organisation already holds.
Is there an AI assurance certification?
Organisations can choose to be certified against ISO/IEC 42001, the AI management system standard, by an independent certification body. The UK government's September 2025 roadmap also sets out work towards an AI assurance profession, including a skills and competencies framework. AIPEX is not a certification body and does not certify.
What is the difference between AI governance and AI assurance?
AI governance sets the rules: who owns each AI system, what it may do, which controls apply and how the board oversees it. AI assurance tests whether those rules work in practice, and communicates the result with evidence. Governance comes first; without it, there is nothing to assure.
Is AI assurance a legal requirement in the UK?
The UK has no single law that requires AI assurance. Its approach relies on existing regulators applying five cross-sector principles. In practice, data protection law, sector regulators, customer contracts and tenders can all require evidence that AI is controlled, which is what assurance provides. This is governance guidance, not legal advice.
How do you prepare for an AI assurance review?
Build an inventory of every AI system in use, name one owner for each, record risk and impact assessments, keep test and monitoring results, collect evidence from suppliers and log incidents and changes. The ISO 42001 Readiness Checklist gives a 15-minute view of how close you are.
Correct as of 28 September 2026. This content reflects the law, official guidance and deadlines as published on that date. The EU AI Act and its guidance, standards and deadlines are still being amended and clarified. If you are reading this after 28 September 2026, check for later amendments, European Commission guidance and harmonised standards before relying on it. It is general information, not legal advice, and AIPEX accepts no liability for decisions taken on it without specific professional advice.
This briefing is general information on AI assurance, drawing on UK government guidance and ISO/IEC 42001, correct at the date last reviewed. It is governance guidance, not legal advice. AIPEX is not a certification or assurance body and does not certify. For decisions about specific AI systems, take advice from qualified advisers.