Definition
Human in the loop is designing an AI system so a person reviews, approves or corrects its work at key points, instead of letting it act fully on its own.
Human in the loop explained
AI agents and automations are fast but can be wrong in ways that are hard to predict. Human-in-the-loop design places people at the points where mistakes would be costly: before an email goes to a customer, before money moves, before a record is deleted, or when the system's confidence is low.
Common patterns include:
- Draft and approve: the AI prepares the work, a person approves or edits it.
- Exception handling: the AI handles routine cases and routes unusual ones to a person.
- Sampling: a person reviews a share of outputs to catch drift over time.
- Feedback: corrections are recorded and used to improve prompts, rules or training data.
The goal is to put people where their judgment adds the most, not to review everything forever. As a system proves reliable on a type of task, review can become lighter for that task while staying strict for higher-risk ones.
Example
Your agentic tool drafts replies to inbound sales enquiries. Instead of sending them automatically, it queues each draft for a rep to approve with one click, and flags enquiries mentioning contracts or pricing exceptions for a senior colleague.
Why it matters
Keeping a person in the loop lets businesses get the speed of AI without handing risky decisions to a system that can make confident mistakes.
Related service
Agentic AI Tools
Custom AI agents and automations that connect to your data and tools, with a human in the loop.
Custom agentic AI toolsPublished by Vidern, founded and led by Malhar Shah. Updated .
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