[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-ai-review-board::en":3,"gloss-cluster-ai-review-board::en":26,"gloss-next-ai-review-board::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"ai-review-board","security","AI Review Board","An AI review board is the standing cross-functional group that decides whether a proposed AI use case may proceed, on what conditions, and who is accountable for it afterwards. It exists because these decisions do not sit cleanly in one function: the questions are simultaneously legal, security, product and technical, and a single team answering them alone will answer only the part it can see.\n\nMembership follows from that. Legal or privacy, security, someone from the engineering side who understands what the system actually does, and a business owner who can say what the use case is worth. Small enough to meet on a real schedule, senior enough that its decisions hold. Boards that grow past a certain size stop deciding and start scheduling.\n\nThe board's value depends on what reaches it. If every use case does, it becomes a queue and teams route around it. The workable pattern is to tie referral to risk tiering: low-risk uses proceed on a self-assessment, and the board sees the ones that automate decisions, touch regulated data, face customers in a high-stakes context, or fall outside existing policy. It also takes the recurring exception requests, which are where policy problems surface first.\n\nIts output should be a decision with conditions and a date, not a discussion. Approved with a named accountable owner, a required evaluation before launch and a review in six months, is a usable outcome. \"The board had concerns\" is not — it leaves the team without a path, and the work continues anyway, now outside the process. Record what was decided and why, because the reasoning is what makes the next similar case fast.\n\nThe board is not the governance programme. It is the escalation point on top of an inventory, a policy and a tiering scheme, and it is only as good as those inputs — a board reviewing whatever teams happen to bring it, without a list of what is already running, is reviewing a sample of unknown size.","An AI review board decides whether a use case proceeds and on what conditions. It works when risk tiering filters what reaches it and it outputs dated decisions.",null,[11,14,17,20,23],{"slug":12,"name":13},"approval-workflow","Approval Workflow",{"slug":15,"name":16},"human-in-the-loop","Human-in-the-Loop",{"slug":18,"name":19},"model-card","Model Card",{"slug":21,"name":22},"red-teaming","Red-Teaming",{"slug":24,"name":25},"vendor-risk-assessment","Vendor Risk Assessment",[27,31,34,37,40,43,46,50,53,56,59,62],{"slug":28,"category":5,"name":29,"updated_at":30},"access-review","Access Review","2026-09-08T21:32:37+00:00",{"slug":32,"category":5,"name":33,"updated_at":30},"ai-governance","AI Governance",{"slug":35,"category":5,"name":36,"updated_at":30},"ai-incident-reporting","AI Incident Reporting",{"slug":38,"category":5,"name":39,"updated_at":30},"ai-risk-tiering","AI Risk Tiering",{"slug":41,"category":5,"name":42,"updated_at":30},"ai-system-inventory","AI System Inventory",{"slug":44,"category":5,"name":45,"updated_at":30},"ai-usage-policy","AI Usage Policy",{"slug":47,"category":5,"name":48,"updated_at":49},"audit-log","Audit Log (Audit Trail)","2026-09-08T21:32:36+00:00",{"slug":51,"category":5,"name":52,"updated_at":49},"blast-radius","Blast Radius",{"slug":54,"category":5,"name":55,"updated_at":49},"break-glass-access","Break-Glass Access",{"slug":57,"category":5,"name":58,"updated_at":49},"bridge-letter","Bridge Letter",{"slug":60,"category":5,"name":61,"updated_at":49},"business-associate-agreement","Business Associate Agreement (BAA)",{"slug":63,"category":5,"name":64,"updated_at":49},"byok","Bring Your Own Key (BYOK)"]