Data governance for AI: Frameworks and best practices

Data governance for artificial intelligence (AI) is crucial as AI systems become integrated into core business functions, necessitating traceable and compliant model decisions based on verified enterprise data. Effective AI data governance involves establishing frameworks and best practices that ensure AI systems access only accurate, compliant data, thereby minimizing risks and aligning with privacy and security regulations. The framework involves setting clear AI goals, assigning cross-functional ownership, classifying sensitive content, enforcing granular access and compliance policies, and continuously refining governance rules. The integration of tools like Box can help centralize security, compliance, and lifecycle controls, fostering responsible AI deployment while protecting sensitive information. These efforts are essential as organizations adapt their governance strategies to support AI and automation, ensuring the technology improves productivity without compromising security, trust, or regulatory compliance.

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