The Evolution from Automation to Agentic AI

Automation has historically played a crucial role in driving industrial, information, and business evolution; employed wherever possible, it improves operational efficiency, and cybersecurity is no different. Advancements in artificial intelligence (AI) have shifted focus beyond the automation of routine, time-consuming tasks toward employing automation to bolster productivity and effectiveness in previously challenging business areas. This shift towards agentic AI, as the industry begins to realize and embrace AI's potential for autonomous decision-making, has drawn considerable interest within the security community. Agentic AI automates tasks in a manner fundamentally distinct from previous approaches to automation.

Agentic AI encompasses models capable of autonomous memory retrieval, utilization of external tools, and interaction with their environment through actions executed in natural language to achieve a defined objective. While information retrieval often involves directing a specialized retrieval agent, agentic AI integrates such functionality independently through a comprehensive internal memory. It interacts with the real world using tools accessible via open APIs and communicates in natural language, issuing instructions to channel actions back to the environment, thereby closing the operational loop.