AI Governance
The framework of policies, controls, accountability structures, and oversight mechanisms that govern how AI systems are developed, deployed, and operated.
What it means
AI governance encompasses all the mechanisms an organization uses to ensure that AI systems behave in alignment with stated policies, ethical standards, regulatory requirements, and business objectives. It covers the full lifecycle: from model development and testing, through deployment, to ongoing monitoring and audit.
Governance at runtime — the operational layer of AI governance — is the set of controls that ensure AI systems comply with policy during execution, not just during development and testing. Runtime governance is where AI governance becomes operationally real.
The gap most enterprises face is between governance documentation (policies, frameworks, risk assessments) and operational enforcement (what actually happens when an AI agent takes an action). Corules closes this gap by making governance operational.
Why enterprise executives need to understand this
Board-level AI governance mandates are creating top-down pressure for CIOs and CTOs to demonstrate that AI governance is operational, not just documented. Regulators and auditors increasingly distinguish between governance frameworks on paper and controls that actively prevent violations at runtime. An AI governance program without runtime enforcement is incomplete.
How Corules implements this
Corules is the runtime enforcement layer of an AI governance program. It translates governance policies (which are documented in natural language) into compiled CEL rules (which are enforced automatically at runtime). Every decision is logged with the policy version that governed it, creating an operational record that demonstrates governance is active, not aspirational.
Frequently Asked Questions
What's the difference between AI governance and AI safety?
AI safety focuses on preventing catastrophic or harmful outcomes from AI systems broadly. AI governance is the organizational and operational discipline of ensuring enterprise AI systems comply with internal policies, regulations, and business rules. Both matter; Corules addresses enterprise AI governance specifically.
How does Corules fit into an existing AI governance framework?
Corules operates as the enforcement execution layer. Most AI governance frameworks (NIST AI RMF, ISO 42001, EU AI Act) require organizations to have controls that actively prevent policy violations. Corules is what makes those controls operational rather than theoretical.
See AI Governance in production
Corules implements every concept in this glossary. Join enterprise teams enforcing policy at runtime — no credit card required.
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