Concept

AI Governance

AI governance is the framework of policies, processes, and organizational structures that ensure AI systems are developed, deployed, and monitored responsibly and in compliance with regulations.

What Is AI Governance?

AI governance encompasses the policies, processes, roles, and tools an organization uses to ensure AI systems are built and operated responsibly — covering data quality, model testing, deployment approvals, monitoring, and regulatory compliance.

How Should Businesses Implement AI Governance?

Effective AI governance includes: defined roles and accountability for AI decisions, documented model evaluation criteria, bias testing protocols, data privacy safeguards, incident response procedures, and regular audits. The EU AI Act, NIST AI Framework, and industry-specific regulations are making governance non-optional. An AI Center of Excellence typically owns governance within larger organizations.

AI governanceAI policyAI compliance

Related Terms

AI Ethics

AI ethics encompasses the principles and practices for developing and deploying AI systems responsibly — addressing fairness, bias, transparency, privacy, and accountability.

AI Alignment

AI alignment is the research field focused on ensuring AI systems behave in accordance with human intentions, values, and goals — preventing unintended or harmful outcomes.

Explainable AI (XAI)

Explainable AI refers to techniques that make AI decision-making processes transparent and understandable to humans, enabling trust, debugging, and regulatory compliance.

AI Center of Excellence (CoE)

An AI Center of Excellence is a dedicated organizational unit that provides AI expertise, governance, best practices, and shared resources to support AI initiatives across an entire company.

Explore Further

Growth Partnership →

Want to apply ai governance in your business?

Take our free AI assessment and get a personalized roadmap for implementing AI strategies that drive real results.

Free AI AssessmentSchedule a Call