The real ROI of predictive maintenance

Predictive maintenance is one of the most over-promised categories in industrial AI. The technology works — but the ROI depends entirely on which assets you target and how mature your maintenance organization already is.

Where it pays back fast

High-value rotating equipment (compressors, large motors, turbines), assets with expensive failure modes (anything that takes a line down), and equipment with predictable degradation patterns. These see 6–12 month payback cycles consistently.

Where it doesn't

Low-cost, easily-replaceable components. Assets with run-to-failure economics. Sites without a functioning CMMS or work-order discipline — the predictions land in nobody's inbox. Fix the basics first.

Honest numbers

We haven't run enough deployments to give you our own figures, and we won't invent them. What the published case studies converge on is that savings come mostly from avoided overtime and emergency parts procurement, not from the dramatic headline numbers in vendor decks. Treat any single percentage with suspicion, including the ones on this page. Ask for the baseline it was measured against.