Human in the loop means designing an AI workflow so a person can review, correct, approve, or take over at a meaningful point. In an agent system, the run may pause before sending an email, publishing a page, changing a database, moving money, or using a sensitive tool. The person sees the proposed action and enough evidence to approve or reject it.
This is more than adding a disclaimer after the output. A real human checkpoint has authority: the action does not continue until the decision is made. It should also appear where human judgment changes the risk, not after the irreversible step has already happened.
The pattern works with guardrails, but the two are not interchangeable. A guardrail automatically blocks or redirects known conditions. Human review handles ambiguity, accountability, and exceptions that cannot be captured reliably in code. Strong workflows use both: automatic checks for clear rules and people for consequential judgment.
Why it matters at your desk. A lawyer using Harvey or Spellbook should remain responsible for the legal conclusion and final redline. Microsoft's move to place a legal agent inside Word brings that review point into the document workflow, where tracked changes and comments can make the proposed edits visible. A team using Workspace Agents in ChatGPT may require approval only for external messages or record changes while letting low-risk research proceed automatically.
Do not require a human click for everything; constant prompts train people to approve without reading. Set checkpoints according to impact, reversibility, confidence, and data sensitivity. The reviewer should know what the agent plans to do, what information it used, and what will happen after approval.