The present invention relates to a system and method for autonomous threat mitigation in agentic artificial intelligence systems using runtime enforcement mechanisms for large language models. The disclosed system comprises a runtime observation processor configured to capture intermediate reasoning states, contextual execution activities, memory access operations, tool invocation requests, and external communication instructions generated by one or more large language model agents during runtime execution. A semantic interpretation processor transforms the captured runtime activities into contextual semantic representations comprising intent vectors, behavioral embeddings, execution dependency structures, and contextual trust indicators. A contextual policy validation processor evaluates the semantic representations against adaptive governance policies, semantic trust boundaries, execution authorization conditions, and operational safety constraints. A threat correlation processor identifies adversarial reasoning patterns, recursive exploitation sequences, prompt injection attacks, memory poisoning activities, unauthorized privilege escalation operations, and anomalous behavioral transitions associated with autonomous execution activities.