Four security principles for agentic AI systems

Agentic AI systems (AI that autonomously connects to software tools and uses large language models as reasoning engines to plan and execute actions) present unique security challenges because they operate at machine speed with real-world consequences, unlike traditional software or human-reviewed generative AI. The main risks are that agents can carry out unintended actions before humans can intervene, and they may not recognize ambiguities or understand unstated policy boundaries like humans do. Security responses don't require entirely new frameworks but should extend existing ones (like NIST's Cybersecurity Framework) with four foundational principles addressing both traditional software components and AI-specific elements.