Procedural documents are common in domains such as technical operations and legal compliance, yet their unstructured and complex logic often hinders comprehension. Converting such texts into flow-charts improves clarity and reduces cognitive load, but existing AI systems typically fall short: they produce static outputs without clarification, fail to adapt to varying document complexity, and lack a principled way to determine when automation is genuinely helpful. To address these challenges, we present IUFlowGen, an AI-assisted, human-in-the-loop system that combines retrieval-augmented generation, LLM reasoning, and graph-based modeling to generate structured and interactive flowcharts. We also introduce a ten-factor rubric to quantify procedural document complexity, enabling adaptive support based on document difficulty. Experiments on 30 documents of varying complexity show that IUFlowGen achieves high accuracy and completeness across all ten factors, demonstrating broader coverage than prior systems. By integrating interactivity, complexity assessment, and clarification, IUFlowGen provides a practical and effective solution for improving user comprehension of complex procedural content.