Runtime security for AI agents

This episode of Techsplainers explores runtime security for AI agents and explains why autonomous systems require deeper protection once they begin operating live across enterprise environments. Building on earlier discussions of nonhuman identities, accountability and runtime risk, the episode focuses on the unique security challenges created when agents reason, decide, execute actions and adapt continuously. It examines the unpredictable action loop at the center of agentic AI, where seemingly simple tasks can expand into tool orchestration, dynamic data access, emergent decisions and multi-agent interactions. From there, the discussion looks at key runtime threats, including agents acting with excessive permissions, untrusted data shaping decisions and goal drift over time. The episode also introduces the A2AS framework and its five foundational control elements, then walks through four critical defense layers: perception, reasoning, action and memory. Along the way, listeners learn how semantic firewalls, dynamic credentials, out-of-band approvals and state protection can help keep agent behavior bounded and accountable. The result is a practical view of how runtime security helps organizations move from AI capability to trusted AI operations. Find more information at https://www.ibm.com/think/insights/agentic-ai-runtime-security Find all the Techsplainers episodes here https://www.ibm.biz/techsplainers-podcast Narrated by Anna Gutowska