NIST AI RMF APPLICATION GOVERNANCE INFRASTRUCTURE MODEL

Risk and benefit balancing

Part of: MG: MANAGE — Risk Response & Communication

Description

AI system risks and benefits are balanced and managed based on expected impact, with risk tolerance aligned to organizational values. Risk management is not risk elimination — it is informed decision-making about acceptable tradeoffs.

Suggested Actions

1

Conduct formal risk-benefit analysis comparing potential harms (technical failures, bias, privacy violations, security breaches) against benefits (efficiency, accuracy improvements, cost reduction, capability expansion)

2

Apply risk treatment strategies systematically: mitigate (implement controls), transfer (insurance, contracts), accept (documented executive approval), or avoid (don't deploy)

3

Ensure residual risks (risks remaining after treatment) align with organizational risk appetite and are explicitly accepted by named individuals with authority to do so

4

Document risk management decisions and rationale for deployment approval with enough detail that the decision can be reviewed and evaluated after the fact

5

Establish quantitative risk thresholds where possible: maximum acceptable bias metrics, minimum performance levels, maximum data exposure scenarios — qualitative risk acceptance is too subjective for consistent governance

6

Re-assess risk-benefit balance after significant incidents, performance changes, or context shifts — the initial assessment is a starting point, not a permanent conclusion

Related Controls

AI Risk Self-Assessment AI Deployment Validation and Approval