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From Autonomy to Accountability: Managing Agentic AI Risks

Agentic AI shifts automation from single-task models to autonomous decision-makers, amplifying risks of misalignment, bias, and data leakage. OWASP’s new guidance equips SMEs with lifecycle security practices, ensuring governance, transparency, and resilience as autonomous agents move from experimentation into production. IT leaders and CISOs should read this article to learn how to secure agentic AI in production using OWASP’s guidance.

Mon., 23. March 2026  |  5 min read

The rise of Agentic AI represents a major shift from single-function models to autonomous agents that can select their own tasks, choose models, and make decisions without direct human instructions. This autonomy amplifies risks, as AI deployments are moving faster than the security controls designed to govern them. Existing risk management programs were not designed to handle the complexity of self-directed AI behavior, and agentic AI amplifies many of the risks already associated with generative AI. Most organizations remain unprepared for the disruptions and vulnerabilities that autonomous agents can introduce, and as one industry observer noted, “autonomy without oversight is a formula for failure”. In response, the OWASP Foundation has released a comprehensive guide for securing agentic AI systems, covering secure architecture, design, development, supply chain security, deployment, and runtime hardening. For IT leaders and CISOs, as agentic AI moves …

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