Human-in-the-loop isn't a compromise — it's the design

There's a common assumption that the end goal of agentic AI is full autonomy — agents that operate with no human involvement at all.

In practice, the systems that perform best in finance and healthcare are designed around a different question: where does human judgment add the most value, and how do we protect that?

This usually means agents handle volume — the high-frequency, well-defined parts of a workflow — while humans handle exceptions, final approvals on high-stakes actions, and anything that requires context the agent doesn't have.

Designed well, this isn't a compromise on capability. It's what makes the system trustworthy enough to actually deploy.