According to a new report, published by KBV research, The Global Predictive Maintenance Market size is expected to reach $94.21 billion by 2032, rising at a market growth of 29.0% CAGR during the forecast period.
The Hardware segment is leading the Global Predictive Maintenance Market by Component in 2024; thereby, achieving a market value of $47.58 billion by 2032. The increasing deployment of IoT sensors, edge computing devices, and advanced monitoring systems has driven the demand for hardware components in predictive maintenance solutions. These hardware devices collect real-time data on equipment performance, including temperature, vibration, pressure, and other critical parameters, enabling accurate failure prediction and timely maintenance interventions. Industries such as manufacturing, oil & gas, energy, and transportation increasingly invest in robust hardware infrastructure to enhance asset reliability and reduce unplanned downtime.
The Cloud segment is anticipating a CAGR of 30.1% during (2025 - 2032). The increasing adoption of cloud computing, IoT, and AI-driven analytics has fuelled the demand for cloud-based predictive maintenance solutions. Cloud deployment offers scalability, remote accessibility, and cost-efficiency, making it a preferred choice for enterprises looking to optimize maintenance operations without heavy infrastructure investments. Cloud-based predictive maintenance solutions enable real-time data collection, AI-driven insights, and seamless integration with enterprise applications, allowing businesses to enhance operational efficiency and reduce downtime. The growing shift toward digital transformation and smart manufacturing has further propelled the adoption of cloud-based predictive maintenance solutions across industries.
The Large Enterprises segment is generating the maximum revenue in the Global Predictive Maintenance Market by Enterprise Size in 2024; thereby, achieving a market value of $64.75 billion by 2032. This dominance is attributed to the substantial resources and capital available to large companies, allowing them to invest in advanced predictive maintenance technologies and tools. Large enterprises typically have complex, high-value machinery and equipment that require continuous monitoring and precise maintenance strategies. As a result, they are more likely to adopt predictive maintenance solutions at scale, leading to higher revenue generation in this segment.
The Artificial Intelligence & Machine Learning segment is registering a CAGR of 28.7% during (2025 - 2032). AI and ML technologies are crucial in enhancing predictive maintenance capabilities by analyzing vast datasets, identifying failure patterns, and providing actionable insights. Industries such as manufacturing, energy, and healthcare leverage AI-driven predictive maintenance to optimize asset performance, reduce operational costs, and minimize downtime. The growing advancements in deep learning algorithms and automation have further strengthened the adoption of AI & ML in predictive maintenance solutions.
The Manufacturing segment is leading the Global Predictive Maintenance Market by End-use in 2024; thereby, achieving a market value of $29.4 billion by 2032. This dominance is driven by the increasing adoption of smart factory solutions, automation, and Industry 4.0 initiatives. Predictive maintenance helps manufacturers minimize unplanned downtime, optimize asset utilization, and reduce maintenance costs by leveraging AI, IoT, and machine learning to monitor real-time equipment health. Additionally, the rising demand for operational efficiency and cost reduction in industrial plants has fuelled the adoption of predictive maintenance solutions.
The Predictive Analytics segment would obtain a CAGR of 28.7% during (2025 - 2032). The growing adoption of AI, machine learning, and big data analytics has significantly enhanced the accuracy and efficiency of predictive analytics solutions. Manufacturing, aerospace, and energy industries heavily rely on predictive analytics to forecast equipment failures, optimize maintenance schedules, and reduce unplanned downtime. The ability to process large datasets and provide real-time actionable insights has made predictive analytics a critical component of modern predictive maintenance strategies.
Full Report: https://www.kbvresearch.com/predictive-maintenance-market/
The North America region dominated the Global Predictive Maintenance Market by Region in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of $31.5 billion by 2032. The Europe region is experiencing a CAGR of 28.6% during (2025 - 2032). Additionally, The Asia Pacific region would exhibit a CAGR of 29.6% during (2025 - 2032).
By Component
By Deployment
By Enterprise Size
By Technology
By End-use
By Application
By Geography
Unique Offerings 
