AI Governance Explained: Key Concepts and Steps to Put It Into Practice

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AI governance refers to the frameworks, policies, and processes organizations use to ensure artificial intelligence systems are developed and deployed responsibly. It covers areas such as accountability, transparency, fairness, and compliance with emerging regulations. Operationalizing AI governance means embedding these principles into day-to-day workflows, tools, and decision-making structures. Organizations are increasingly urged to assign clear ownership of AI risks and establish monitoring mechanisms for deployed models. As AI adoption grows, structured governance is seen as essential for managing legal, ethical, and reputational risks.

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