In plain English
AI governance answers practical questions: who is accountable for AI risk, which AI systems the institution has and how risky each is, how they are tested and monitored, how data and privacy are protected, how vendors are managed, and what happens when something goes wrong.
Frameworks such as the NIST AI Risk Management Framework (govern, map, measure and manage) and ISO/IEC 42001 (an AI management system standard) give structure. Some regulators have issued specific expectations, such as the Central Bank of the UAE's February 2026 guidance for licensed financial institutions, and the EU AI Act sets legal requirements for AI used in the EU.
Why it matters to a board
Boards are increasingly expected to oversee AI use and to show that someone is accountable, that risks are rated, and that there is evidence the controls work.
Common mistakes
- Treating AI governance as a technology team matter.
- An AI policy with no inventory behind it.
- Governance at approval only, with no monitoring afterwards.
- Ignoring AI embedded in vendor products and tools staff use themselves.
What the standards and regulators say
- NIST Artificial Intelligence Risk Management Framework 1.0 (NIST AI 100-1)
- ISO/IEC 42001:2023: Artificial intelligence management system standard
- Central Bank of the UAE: Guidance Note on Consumer Protection and Responsible Adoption and Use of Artificial Intelligence and Machine Learning (11 February 2026)
- European Union: Regulation (EU) 2024/1689 (the AI Act). Application dates have been changed, so check the current timetable