State of Predictive Maintenance 2026

Predictive maintenance has moved from pilot projects to budgeted, scaled deployment. The market is growing near 30% a year, AI adoption in manufacturing has roughly doubled in two years, and the cost barrier to starting keeps falling. This report pulls together the public numbers on where predictive maintenance stands in 2026 and what is driving it.

The market is growing near 30% a year

2025$14.3B2033 (proj.)$98.2B
Global predictive-maintenance market size, USD billion (Grand View Research).

Source: Grand View Research — Predictive Maintenance Market Size & Forecast (2025)

The global predictive-maintenance market was estimated at about USD 14.3 billion in 2025 and is projected to reach roughly USD 98 billion by 2033 — a compound annual growth rate near 28%. That is one of the fastest growth rates of any industrial-software category, and it reflects a genuine shift in how plants approach reliability rather than a passing trend.

AI adoption is the engine underneath it

Enterprise AI 202335%Enterprise AI 202567%Manufacturers using AI51%
Share of organisations using AI (Stanford AI Index 2025; manufacturer survey).

Source: Stanford HAI — AI Index Report 2025 (2025)

Predictive maintenance rides on the broader adoption of industrial AI. Enterprise AI use jumped from about 35% of organisations in 2023 to roughly 67% in 2025, and surveys put the share of manufacturers using AI in some form around half. As models, sensors and connectivity get cheaper and more capable, condition monitoring and analytics become standard tooling rather than experiment.

From scheduled servicing to condition-based intervention

The underlying change is a move away from fixed-interval maintenance — which both over-services healthy machines and misses faults that develop between visits — toward condition-based and predictive strategies that intervene only when the data shows a fault developing. The workhorse techniques are vibration analysis, thermography, oil analysis, ultrasound and process-data analytics, each catching different faults at different stages.

FAQ

What is predictive maintenance?

Predictive maintenance uses sensor data and analytics to predict when equipment will fail, so maintenance is done just before failure — not on a fixed schedule and not after a breakdown. It reduces unplanned downtime and avoids unnecessary scheduled work.

Is predictive maintenance worth it?

For critical, continuously-running assets where failure is costly, predictive maintenance typically pays back by cutting unplanned downtime and extending intervals on healthy machines. For low-consequence assets, simpler strategies are often more economical — the value depends on asset criticality.

Sources

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