A complete guide to agentic AI governance

Agentic AI governance is the structured management of autonomous AI systems that execute tasks on behalf of organizations, emphasizing authority control rather than just output quality. This approach is essential for roles like chief AI officers and CISOs who manage workflows involving content and data, as it addresses risks such as unauthorized actions, data exfiltration, and privilege escalation. Unlike traditional AI governance, which focuses on the quality of model outputs, agentic AI governance ensures that actions are authorized and within defined boundaries. The guide provides an eight-step framework for implementing agentic governance, highlighting the importance of defining the agent's scope, maintaining strict identity and access boundaries, and establishing human oversight thresholds. It also discusses how Box manages agentic AI governance at the content layer by ensuring that agents operate within the same security and compliance boundaries as human users. The document stresses the need for continuous monitoring to prevent authority expansion and outlines the responsibilities of various stakeholders, including model providers, platform operators, integrators, and deploying organizations, to ensure accountability when autonomous agents are deployed.

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