Predictive Maintenance Market worth $16.74 billion by 2031
The report "Predictive Maintenance Market by Monitoring Infrastructure (Sensors & Sensing, Imaging & Inspection Devices, Edge Monitoring, Connectivity Hardware), Software (APM, IIoT, Digital Twin, AI-driven Predictive Maintenance Platforms) - Global Forecast to 2031" is expected to grow from USD 9.71 billion in 2026 to USD 16.74 billion by 2031, reflecting a CAGR of 11.5% during the forecast period.
Browse 457 market data Tables and 80 Figures spread through 377 Pages and in-depth TOC on "Predictive Maintenance Market by Monitoring Infrastructure (Sensors & Sensing, Imaging & Inspection Devices, Edge Monitoring, Connectivity Hardware), Software (APM, IIoT, Digital Twin, AI-driven Predictive Maintenance Platforms) - Global Forecast to 2031"
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The predictive maintenance market is expanding rapidly as organizations modernize asset management strategies and adopt intelligent monitoring systems across industrial operations. Growth is fueled by the increasing need to minimize equipment downtime, optimize maintenance schedules, and improve operational efficiency through data-driven insights. Demand intensifies as enterprises deploy connected sensors and advanced analytics to continuously evaluate equipment performance across distributed facilities. The market is further shaped by trends such as the integration of artificial intelligence within asset management platforms and the adoption of cloud-enabled maintenance solutions that enhance scalability. These advancements enable organizations to detect potential equipment issues earlier, improve maintenance accuracy, and strengthen overall asset reliability across manufacturing, energy, and transportation environments.
By monitoring infrastructure, the sensors & sensing devices segment is poised to dominate the market in 2026.
Sensors and sensing devices hold the largest market share among monitoring infrastructure components due to their widespread deployment across industrial equipment and connected machines. These devices capture real-time operational parameters, such as vibration, temperature, pressure, and acoustic signals, enabling continuous equipment condition monitoring. They are widely implemented across manufacturing plants, energy facilities, and transportation systems to support predictive maintenance strategies. Integration with industrial IoT platforms and asset management systems enables automated data collection and improved visibility into equipment performance. The increasing deployment of smart manufacturing systems, connected machinery, and digitalized industrial operations further strengthens the dominant position of sensors and sensing devices in the predictive maintenance market.
By monitoring technique, visual inspection is expected to register the fastest growth during the forecast period.
Visual inspection is expanding rapidly as computer vision, drones, and AI-based inspection systems are adopted in industrial environments. These technologies allow organizations to inspect equipment, infrastructure, and production assets without direct manual intervention. Automated visual inspection can identify surface defects, leaks, corrosion, and structural damage that may not be detected through traditional sensors. As industries adopt smart manufacturing and remote monitoring practices, visual inspection solutions are increasingly used to improve fault detection, reduce manual inspection time, and enhance worker safety.
By region, North America is estimated to account for the largest market during the forecast period.
North America is expected to dominate the predictive maintenance market due to early adoption of industrial IoT, artificial intelligence, and advanced analytics across asset-intensive industries. The region benefits from leading technology providers and strong investments in digital asset management and smart manufacturing. Organizations across the manufacturing, energy, aerospace, and transportation sectors widely deploy predictive maintenance platforms to improve equipment reliability and reduce operational downtime. Mature cloud infrastructure and high technology awareness further support the large-scale deployment of asset performance management solutions. Continuous investments in connected industrial systems and data-driven maintenance strategies strengthen North America’s leading position in the predictive maintenance market.
The major players in the predictive maintenance market include ABB (Switzerland), Honeywell (US), Schneider Electric (France), AWS (US), IBM (US), Google (US), Microsoft (US), Hitachi (Japan), GE (US), and Oracle (US).
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