Dynamic enforcement is the practice of applying policies, permissions, or controls in real time, based on current conditions, context, or risk factors. Unlike static rules, it adapts continuously to changing circumstances to maintain security, compliance, and operational efficiency.

Why it matters: Dynamic enforcement reduces the risk of unauthorized actions, ensures policies remain effective in complex environments, and supports responsive decision-making. In AI systems, it is especially critical for autonomous agents, where actions occur at machine speed and must be continuously evaluated against evolving conditions.