Human-in-the-loop: A hybrid orchestration model for intelligent automation

AI-powered intelligent automation makes business processes better, but it has trouble with tasks that are only partially structured or are not clear. This research presents a hybrid Human-in-the-Loop (HITL) orchestration model that integrates AI efficiency with human supervision to enhance decision-making accuracy. We looked at three modes—manual, semi-automated, and fully automated—across key metrics using a simulated document processing case that included classification, summarization, and PII extraction on a low-code automation platform. The semi-automated mode had a 95.6 percentage accuracy rate, cut the average processing time to 2.9 seconds per page, and gave a 38 percentage return on investment. This mode was better at balancing speed and reliability than the other modes. The results show that HITL orchestration greatly improves contextual understanding and compliance while still keeping the benefits of automation. The framework offers a scalable basis for responsible and adaptive enterprise automation that is in line with new trends in low-code orchestration and hybrid intelligence.