Give your board the information, structures, and confidence to govern AI adoption with authority. Independent AI risk briefings, governance maturity review, and assurance reporting built for directors who are accountable for outcomes they need to understand.
We conduct an independent review of where AI is operating across the organisation and assess the current governance maturity — what policies exist, what oversight structures are in place, and where the significant gaps are. Management cannot provide independent assurance about its own AI programme.
A board-ready AI briefing document — structured for non-technical directors — covering AI exposure, material risks, governance status, and what the board needs to do. Plus an AI assurance dashboard and reporting template for ongoing structured oversight.
We define what requires board approval, what can be delegated to management, and what must be escalated. Boards in regulated industries — financial services, health, professional services — increasingly face regulatory expectations around AI governance that require demonstrable active oversight.
For board assurance, APIG provides a structured framework for examining where AI is operating across the organisation and what the board needs to govern — at each of the four dimensions where AI creates accountability obligations.
Board AI assurance is the structured process of giving a board or audit and risk committee the information, frameworks, and oversight structures they need to govern AI adoption with confidence. It covers understanding the AI risk exposure, reviewing governance maturity, establishing reporting standards, and defining what the board needs to see — and how often — to exercise meaningful oversight.
AI introduces a set of risks and oversight obligations that existing board reporting does not address well — model transparency, data provenance, bias risk, vendor dependency, and AI system drift are not categories that standard financial or operational reporting covers.
The six questions that matter most are: Where is AI operating in our organisation? Who is accountable for AI outcomes? What are our material AI risks? How are those risks being managed? Are we meeting our regulatory and ethical obligations? And what would we do if something went wrong?