The Business AI Governance Test is a practical checklist designed to help a business establish whether the protections surrounding its use of artificial intelligence actually work in practice. It is not a guide to writing AI policies or building technical controls. Instead, it asks a more direct question: what should a business be able to demonstrate before it can reasonably claim that its use of AI is governed?
The test contains 25 questions divided into two sections. The first examines control and accountability. It asks whether people can reject or challenge AI decisions, obtain effective human help, leave an AI-enabled service safely and receive the same protection regardless of price, location, language or other circumstances. It also examines whether safeguards actually work, whether responsibility can be enforced across several companies and whether the business can obtain reliable evidence showing what happened when something goes wrong.
The second section examines reliable information and protection across connected systems. It asks whether the AI makes uncertainty clear, provides genuine sources, explains important limitations and changes factual answers only when there is evidence to justify the change. It also tests whether mistakes, disputed information or compromised systems can be contained before problems spread, and whether rights and protections remain effective when information moves between different systems, providers or countries.
Each question is answered YES or NO, but a YES must be supported by evidence. A policy statement, contract clause, dashboard option or provider promise is not enough by itself. The business needs to be able to show that the protection works for the particular AI service and business use being assessed. If the answer is NO, unknown or unsupported, the test treats that as a gap requiring investigation or corrective action.
The benefit is practical. Completing the test helps a business understand what it can genuinely rely on, where protections are weak or unproven, and where a failure could lead to unnecessary costs, unresolved complaints, disruption, bad decisions or loss of trust. Repeating the assessment when systems, providers or uses change also helps reveal when a protection that once worked has quietly become weaker.
A public reference standard that defines AI governance as a measurable structural condition, moving beyond policy statements to test whether control, accountability, traceability and integrity can be demonstrated in practice across the AI lifecycle.
A quantitative AI governance metric designed to measure how much of an AI system remains provable when models, APIs, vendors or other upstream dependencies change. ERR focuses on traceability, reconstructability, version fidelity and dependency proof to assess whether governance can survive change.
The Business AI Governance Test is a practical YES/NO checklist designed to establish whether the protections surrounding a business's use of artificial intelligence can actually be demonstrated in practice rather than relying only on policies, contracts, provider claims or technical safeguards.
A practical governance test examining whether a business can maintain critical services if access to an external AI provider is suddenly restricted or withdrawn because of provider decisions, government action, sanctions, trade restrictions or geopolitical disruption.
A public reference framework for testing whether important AI protections actually work in practice, focusing on control, accountability, business dependence and effective oversight rather than relying on policies, promises or formal safeguards alone.
A practical business checklist examining why intervention in AI use may become necessary, what it is intended to protect and whether the organisation retains the authority, information and practical ability to act before consequences become unmanageable.