Global AI-Driven Predictive Maintenance Market Set For 15.5% Growth, Reaching $1.56 Billion By 2028
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What Does Recent History Reveal About The AI-Driven Predictive Maintenance Market Size?
The artificial intelligence AI-driven predictive maintenance market has blossomed in recent years. It has grown from a value of $0.76 billion in 2023 to a projected $0.88 billion in 2024, with a compound annual growth rate CAGR of 15.0%. This growth in the historic period can be attributed to an increased demand from large enterprises, concerns over asset maintenance, technological awareness, and preferences among small and medium enterprises SMEs.
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Do Projections Indicate Continued Growth For The AI-Driven Predictive Maintenance Market?
Yes, the AI-driven predictive maintenance market is expected to see accelerated growth in the next few years. It's forecasted to reach $1.56 billion by 2028, indicating a compound annual growth rate CAGR of 15.5%. Various factors contributing to this predicted growth include growing preferences for predictive maintenance solutions, the push for more efficient customer-oriented processes, ageing infrastructure, and increasing complexities in a variety of industries. Major trends to consider during this period include enhanced human-AI collaboration, integration with 5G networks, AI-enhanced predictive maintenance in supply chains, and integration with circular economy practices.
Does The Adoption Of Cloud-Based Solutions Impact The AI-Driven Predictive Maintenance Market?
The growing adoption of cloud-based solutions is anticipated to significantly propel the growth of the AI-driven predictive maintenance market going forward. Cloud-based solutions—affordable software or services hosted on the cloud—provide businesses with efficient, scalable, and accessible tools without requiring substantial upfront infrastructure investments. Adoption of these solutions is advantageous for AI-driven predictive maintenance; they offer scalable computing power and storage, processing large amounts of sensor data in real time, and enable accurate predictions of equipment failures.
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Which Companies are Dominating The AI-Driven Predictive Maintenance Market?
Major companies operating in the artificial intelligence AI-driven predictive maintenance market are Microsoft Corporation, Hitachi Ltd., General Electric Company, International Business Machines Corporation, Schneider Electric SE, Honeywell International Inc., ABB Ltd., Emerson Electric Co., HCL Technologies, Rockwell Automation Inc., Flowserve Corporation, SAS Institute Inc., Fluke Corporation, Cloudera Inc., TIBCO Software Inc., RoviSys Company, Aspen Technology Inc., C3.ai Inc., SparkCognition Inc., Uptake Technologies Inc., Gastops Ltd., Senseye Ltd., MachineMetrics Inc., Presenso, MachineStalk Inc., LNS Research Inc., Pivotal Software Inc., and Guidewheel.
What Are The Emerging Trends in The AI-Driven Predictive Maintenance Market?
Major companies are currently focusing on developing technologically advanced solutions, such as cost-effective AI-driven predictive maintenance solutions, to boost operational efficiency and reduce maintenance costs. For instance, in July 2024, Guidewheel, a U.S.-based software company, launched Scout, an AI-powered FactoryOps platform designed to enhance manufacturing operations by integrating AI technologies. This innovative tool integrates with existing systems to monitor machine performance data for early detection of anomalies, improving its predictive accuracy over time.
How Is The AI-Driven Predictive Maintenance Market Segmented?
The AI-driven predictive maintenance market is segmented by:
1 Solution: Integrated Solution, Standalone Solution
2 Deployment: Cloud, On-Premise
3 Industry: Automotive And Transportation, Aerospace And Defense, Manufacturing, Healthcare, Telecommunications, and Other Industries.
Which Region Holds The Largest Share in The AI-Driven Predictive Maintenance Market?
North America was the largest region in the AI-driven predictive maintenance market in 2023. However, regions like Asia-Pacific, Western Europe, Eastern Europe, South America, Middle East, and Africa also offer substantial contributions.
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