Topic

Runtime-Boundaries

Runtime boundaries are technical and operational limits established during the execution of AI systems to control behavior, outputs, and resource consumption in production environments. These include mechanisms like token limits, response timeouts, rate limiting, and content filters that prevent models from exceeding intended parameters. For enterprise AI governance, runtime boundaries are critical for ensuring predictable system behavior, containing costs, mitigating hallucinations or harmful outputs, and maintaining compliance with established policies without requiring model retraining.

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Corporate PolicyUS2026-06-22

Palo Alto Networks Frames Delegated Authority as the Core Risk in Agentic AI Governance

Palo Alto Networks has published a practitioner guide defining agentic AI governance around the structured management of delegated authority, runtime access boundaries, and human oversight thresholds. The guide specifies key steps including agent scope definition, pre-deployment impact assessments, and explicit accountability mapping. It positions these controls as essential to preventing agents from exceeding their intended operational boundaries.

agentic-ai delegated-authority runtime-boundaries human-oversight agent-governance