Who should own AI governance in a business?
AI governance needs a named accountable owner supported by business, IT, security, privacy and relevant specialist teams. Ownership should cover approved uses, data access, evaluation, human oversight and ongoing changes. It should not be left entirely to the person who builds the assistant.
Keep a record of the use case
Document the purpose, intended users, systems, data and expected actions. Identify decisions the system must not make independently. A simple inventory helps the business understand where AI is being used and who is responsible.
Review risk in context
Consider the effect of an incorrect answer, inappropriate disclosure or failed action. The necessary controls depend on the workflow and its consequences. Relevant legal and sector requirements should be assessed by qualified people for that context.
Define the release decision
Name the reviewers and the evidence needed before launch. Include quality tests, access controls and a plan for incidents or complaints. Keep the acceptance record so later changes can be judged against the original scope.
Govern changes after launch
New data sources, tools or user groups can change the risk. Decide which changes require review and who can suspend the system if there is a problem. Maintain a human escalation route for users.
Governance should help a useful project operate responsibly. It is most effective when its responsibilities are part of normal delivery and support, rather than a separate document nobody uses.
Put this guidance to work.
Explore the relevant emtech service, then discuss the scope that fits your business.