The process of identifying, assessing, and mitigating risks associated with AI systems.
A continuous, structured cycle - risk identification, assessment, mitigation planning, implementation, and monitoring - embedded into AI lifecycle practices to keep emerging threats in check.
Before launching an autonomous warehouse-robot system, a logistics company identifies hazards (collisions, theft, system outages), assesses likelihood and severity, applies safeguards (safety zones, encrypted comms, fail-safe overrides), and tracks key risk indicators via a live dashboard.
