A hybrid AI approach combining computer vision, graph databases, and generative AI transforms maintenance planning for Piping and Instrumentation Diagrams (P&IDs), which are complex technical drawings that remain trapped as static PDFs requiring 3 to 8 hours of manual analysis per diagram. For example, 511 industrial P&ID documents may contain 1,397,710 distinct visual patterns, 457,861 circular symbols, 320,583 dense connections, 181,265 horizontal lines, and 64,314 specialized patterns. The hybrid approach enables engineers to upload P&ID diagrams and gain engineer-level insights, recommendations, and maintenance plans within minutes, replacing manual tasks through a human-above-the-loop process. According to McKinsey, 80% of manufacturers reported cost reductions of up to 10% from AI usage, with the remaining 20% seeing improvements of 10-19% or higher. For maintenance planning, McKinsey states AI has the potential to increase workforce productivity by up to 2x by automating nearly 70% of routine tasks and improve accessibility of maintenance documentation by scaling through thousands of P&ID documents.