Human-in-the-Loop (HITL) review workflows integrate human oversight into AI processes to ensure accuracy and quality. Humans validate, correct, or refine AI outputs, creating a feedback loop that improves system performance and reliability.
AI generates initial results which are then reviewed by human experts. The human feedback is incorporated back into the AI model or system, refining algorithms and decisions. This iterative process balances automation efficiency with human judgment.
For AI product managers, HITL workflows improve user trust by reducing errors and bias. They enable scalable quality control without fully manual processes, optimize cost by focusing human effort where needed, and help meet regulatory or ethical requirements, all while maintaining acceptable latency.