AI governance shifts to runtime as always-on agents spread
As AI agents move from occasional tools to always-on systems that act continuously in the background, governance frameworks are shifting focus from how models are built to how they behave at runtime, in real time.
Why this matters: Most AI rules were written for models that answer questions when asked. Agents that run all the time are different. They make decisions, take actions, and touch data without waiting for a human to press a button. That changes the accountability problem completely. You cannot just audit the training data and call it done. You have to watch what the system is doing right now, with real access, on live systems. The governance infrastructure most companies have is not built for that.
Who should care: AI governance · Lawyers · Administrators · General readers · Policy
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