AI Risk Management
AI risk management is the discipline of identifying, assessing, mitigating, and monitoring risks specific to AI systems across their entire lifecycle, sitting as a function within the broader AI governance program.
What AI Risk Management Covers
AI risk management addresses risks that span several categories: security risks (prompt injection, model extraction, adversarial attacks), governance risks (unclear ownership, undocumented systems, unauthorized use), compliance risks (regulatory non-conformance, disclosure gaps), and operational risks (model drift, degraded outputs, system unavailability).
See AI risk management: defining, measuring, mitigating the risks of AI for a comprehensive treatment.
Why AI Risk Management Is a Distinct Discipline
AI risks do not fit neatly into existing risk categories. They span technology, legal, ethical, and business dimensions simultaneously. A single AI incident can produce security consequences, compliance consequences, reputational consequences, and customer harm at the same time. Traditional risk functions were not designed for this cross-cutting profile.
The NIST AI RMF and ISO/IEC 42001 both treat AI risk management as a first-class program, distinct from but connected to enterprise risk management.
Risk Management and Governance
AI risk management sits inside AI governance, not alongside it. See AI risk management as a function of AI governance: a holistic approach. Governance defines the framework, risk management operates inside it.
How Kovrr Approaches AI Risk Management
Kovrr's AI Security and Governance Platform operationalizes AI risk management by connecting discovery, assessment, control monitoring, and quantified exposure into a single workflow. Risks are surfaced from actual telemetry rather than manual reporting, and mitigation decisions are prioritized against modeled exposure.
Related Terms
Full AI Visibility. Full Control. One Connected Platform.
Enterprise AI is expanding faster than most governance programs can track. Kovrr connects every AI signal across browser, endpoint, network, identity, and vendor systems into a single platform so security, governance, and risk teams work from the same evidence.
