AI governance and AI security address two different dimensions of responsible enterprise intelligence. AI governance establishes how intelligence systems are governed, controlled, monitored, and used responsibly, covering policies, accountability, risk management, compliance, transparency, and oversight. AI security focuses on protecting intelligence systems from threats and attacks across models, data, applications, infrastructure, and access.
This infographic explains the difference between AI governance and AI security, highlighting their focus areas, key risks, and essential controls. Governance risks can include regulatory non-compliance, unclear accountability, uncontrolled use, and transparency gaps. Security risks include prompt injection, data leakage, model manipulation, and unauthorized access.
Together, governance and security form complementary layers of an enterprise AI risk management strategy. Governance defines acceptable use, accountability, and oversight, while security protects the underlying systems and data from compromise.
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