AI governance glossary
A practical vocabulary for the people who approve, build, buy, audit, and oversee AI—each definition linked to the evidence behind it.
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6 entriesAI governance
The system of decision rights, controls, accountabilities, and evidence used to direct and oversee AI.
OperationsAI incident
An event in which the development, use, or malfunction of AI directly or indirectly leads to actual harm.
OperationsAI inventory
A controlled register of AI systems, models, use cases, owners, dependencies, and risk information.
FoundationsAI management system
AIMSInteracting policies, objectives, roles, and processes for managing responsible AI across an organization.
FoundationsAI system
A machine-based system that infers how to generate outputs that can influence physical or virtual environments.
Risk & assuranceAlgorithmic impact assessment
AIAA structured assessment of an automated system’s likely impacts, risks, and required mitigations.
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1 entryD
2 entriesE
1 entryF
2 entriesG
1 entryH
2 entriesM
1 entryP
1 entryR
1 entryS
1 entryT
1 entryDefinitions built for decisions, not memorization.
Legal terms follow their controlling text. Practice terms are synthesized from standards, official guidance, and peer-reviewed or foundational research. Every entry separates a working definition from its operational meaning.
Start with primary authority.Legislation, government guidance, and recognized standards anchor the wording.
Translate without flattening.Plain language sits alongside the nuance needed for real governance decisions.
Show the evidence trail.Each term links to official material and relevant research where it adds practical depth.