Human-in-the-Loop (HITL)
A design pattern in which humans review and approve AI decisions at designated points in a workflow, used for high-stakes or low-confidence cases where full automation is inappropriate.
How it works
Human-in-the-loop is not a fallback for when AI is bad. It is a deliberate architecture for workflows where the AI does the routine work and humans handle the cases where judgment, accountability, or regulation requires it. Examples: clinical-letter triage where the AI classifies and the consultant signs, AML transaction monitoring where the AI surfaces patterns and the analyst investigates, FCA Consumer Duty reporting where the AI drafts and the senior named individual approves. The design challenge is to get the threshold right: too aggressive on automation and high-stakes errors slip through; too conservative and the human reviewer becomes a bottleneck. Confidence calibration, exception routing, and audit trails are the structural elements that make HITL work in production. Ayoob AI builds HITL into every regulated workflow.
Related terms
Workflow Automation
The use of software to execute a defined sequence of business operations (data extraction, validation, routing, action) end-to-end without human intervention except at designated review points.
Document Triage
The classification and routing of incoming documents (clinical letters, legal correspondence, customer requests) by topic, urgency, and required action, with the AI handling routine cases and escalating exceptions.
Hallucination
A language model output that is fluent and plausible but factually incorrect, fabricated, or unsupported by source material, occurring when the model generates content based on training-data patterns rather than grounded evidence.
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