AI Governance
Last Updated: July 29, 2026 | By Mihail Sebastian | AI Dictionary
The structures, policies, and processes an organization uses to direct and control its AI – the umbrella over policy, compliance, and regulation.
What is AI Governance?
AI governance is the system of structures, policies, and processes an organization uses to direct, monitor, and take accountability for how it develops and uses artificial intelligence. It is the umbrella term of this field: regulation, policy, and compliance each name one piece of the apparatus, and governance names the whole.
How AI Governance Works
Governance operates in layers. Principles at the top state what the organization will and will not accept from AI, such as fairness in decisions about people. Policies translate the principles into rules specific enough to check.
Processes apply the rules to real systems: use-case intake, review boards, impact assessments, audits, incident response. Monitoring closes the loop by watching deployed systems for drift, bias, and failures the reviews missed.
The neighboring terms divide up this territory.
AI regulation is imposed from outside: rules that public authorities write and enforce. A policy is a rule the organization writes for itself. Compliance is the work of meeting both and proving it.
Governance is what connects them, and it also covers ground no law requires yet, such as ethical commitments and escalation paths for novel uses.
Example of AI Governance
A company wants to deploy an AI resume screener, and its governance system touches the project at every stage. At intake, the AI review board classifies the use case as high-impact because it affects people’s livelihoods.
Policy then requires bias testing across demographic groups before launch and human review of every automated rejection. The vendor contract obliges the supplier to hand over technical documentation, since the board cannot assess a black box.
After launch, quarterly monitoring compares selection rates across groups, and every screening decision lands in an audit trail. When the EU AI Act’s high-risk obligations for hiring tools reach the company, most of the required evidence already exists – governance built the compliance case before regulation asked for it.
FAQ
Who is responsible for AI governance in an organization?
Accountability sits with senior management and the board, as with any other governance domain. Day-to-day ownership varies: some organizations appoint a chief AI officer or governance lead, others assign the work to a cross-functional committee spanning legal, risk, security, and engineering. What matters is that a named person or body answers for each system.
Is AI governance required by law?
No law mandates “AI governance” by name, but several require its components. The EU AI Act obliges providers of high-risk systems to run risk management, keep technical documentation, and design for human oversight, which amounts to governance in all but name. Organizations outside those rules still build it because customers, insurers, and boards ask for the evidence.
Related AI terms: Policy · Compliance · AI Regulation · AI Law · Responsible AI
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Mihail Sebastian — Writes about AI governance, regulation, and the technology behind them. Placeholder bio — replace with a real credential line. About