Not every identified AI risk can be eliminated. When an organization decides that remaining risk is tolerable, the decision should be explicit, owned, time-bounded where appropriate, and supported by evidence rather than disappearing into meeting notes.
Describe the residual risk clearly
Record the scenario, affected people or processes, potential impact, existing controls, evidence reviewed, and uncertainty that remains. Avoid labels such as low or acceptable without explaining what they mean in context.
Name the decision owner
Risk acceptance should be made by a role with authority appropriate to the impact. Technical teams can provide evidence, but they should not silently assume business, legal, safety, clinical, employment, or regulatory authority they do not hold.
Record conditions and limits
Document scope, approved users, data boundaries, human review requirements, monitoring signals, escalation triggers, and circumstances that invalidate the acceptance.
Set review triggers
Revisit the decision when models, vendors, data, integrations, use cases, affected populations, laws, controls, or observed performance change. NIST AI RMF 1.0 uses Govern, Map, Measure, and Manage functions and treats risk management as an ongoing lifecycle activity.
Connect acceptance to monitoring
Residual risk should remain observable. Link the record to metrics, incidents, complaints, testing, or other evidence that can show when assumptions no longer hold.
Related knowledge
Use this with AI Use-Case Approval Records, AI Change Impact Reviews, AI Monitoring Plans, and AI Human Oversight Design.
References
This resource supports operational governance and does not establish legal compliance or replace qualified legal, regulatory, clinical, financial, employment, safety, accessibility, privacy, or other professional review.