Al-Driven Predictive Maintenance Market Revenue Trends and Growth Drivers

Al-Driven Predictive Maintenance Market by Solution (Integrated Solution, Standalone Solution), Deployment Mode (Cloud, On-premises), Technique (Vibration Analysis, Infrared Thermography, Oil Analysis), Organization Size, Industry - Global Forecast to 2030

Report Code: UC-SE-6886 Jun, 2025, by marketsandmarkets.com

The predictive maintenance market driven by AI technology continues to grow substantially because industries are adopting advanced solutions, including IoT, ML, and AI technologies. Through advanced AI analytical solutions, organizations use historical and present-day data inputs to determine when equipment will fail ahead of time. The predictive maintenance procedure decreases operational delays and overall equipment performance while optimizing operational expenditures. AI-driven predictive maintenance solutions are rapidly gaining commercial interest because industries actively seek better productivity and improved asset performance.

The market offers integrated solutions and standalone solutions to address different customer requirements. Integrated solutions connect with already existing systems, whereas standalone solutions operate independently. These solutions became popular in the manufacturing and aerospace industries due to their need for complex machinery requirements. Companies operating small businesses often select standalone predictive maintenance solutions over other options because these systems offer independent capabilities. Machinery durability improves while maintenance expenses decrease when these solutions collaborate.

Several industries, such as energy & utilities, oil & gas, automotive & transportation, aerospace, manufacturing, healthcare, and telecommunications, utilize predictive maintenance systems powered by AI technologies. AI-driven predictive maintenance automotive industries to track vital vehicle components that leads to better results for fleet operations while preventing unplanned equipment failure. The aerospace sector employs these solutions to efficiently maintain aircraft systems, decreasing the probability of aircraft failures in flight. The manufacturing sector adopts predictive maintenance systems to manage production stations and minimize machine stoppages, which benefits operational productivity. Predictive maintenance plays a vital role in healthcare in sustaining the unhampered operation of medical equipment and diagnostic tools, which results in better patient care.

The AI-driven predictive mainteance market continues to grow immediately in regions with strong industrial growth, including North America, Europe, and Asia Pacific. North American industries' growing need for enhanced operational efficiency through digital transformation strategies requires predictive maintenance solutions. The European market is experiencing increasing growth due to manufacturing automation and the ongoing implementation of Industry 4.0 technology. Predictive maintenance implementation has experienced rapid growth across Asia-Pacific owing to rising automotive, electronics manufacturing, and telecommunications sectors.

Hence, the AI-driven predictive maintenance market will experience persistent growth because industrial facilities focus on asset performance optimization, cost-efficient maintenance, and operational improvements.

The major players in the AI-driven predictive maintenance market are Siemens (Germany), GE Vernova (US), SAP SE (Germany), C3.ai, Inc. (US), and ABB (Switzerland).

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TABLE OF CONTENTS

1 Introduction

1.1. Study Objectives

1.2. Market Definition and Scope

1.2.1. Inclusions and Exclusions

1.3. Study Scope

1.3.1. Markets Covered

1.3.2. Geographic Segmentation

1.3.3. Years Considered for the study

1.4. Currency

1.5. Limitations

1.6. Stakeholders

2 Research Methodology

2.1. Research Data

2.1.1. Secondary Data

2.1.1.1. Major Secondary Sources

2.1.1.2. Key Data from Secondary Sources

2.1.2. Primary Data

2.1.2.1. Primary Interviews with Experts

2.1.2.2. Key Data from Primary Sources

2.1.2.3. Key Industry Insights

2.1.2.4. Breakdown of Primaries

2.2. Market Size Estimation

2.2.1. Bottom-Up Approach

2.2.1.1. Approach for Capturing Market Share by Bottom-Up Analysis (Demand Side)

2.2.2. Top-Down Approach

2.2.2.1. Approach for Capturing Market Share by Top-Down Analysis (Supply Side)

2.3. Market Breakdown and Data Triangulation

2.4. Research Assumptions

2.5. Risk Assessment

2.6. Limitations of Research

3 Executive Summary

4 Premium Insights

5 Market Overview

5.1. Introduction

5.2. Market Dynamics

5.3. Trends/Disruptions Impacting Customer’s Business

5.4. Pricing Analysis

5.4.1. Average Selling Price Trend of Key Players, By Solution

5.4.2. Average Selling Price Trend, By Region

5.5. Value Chain Analysis

5.6. Ecosystem Analysis

5.7. Technology Analysis

5.8. Patent Analysis

5.9. Trade Analysis

5.10. Key Conferences and Events (2024-2025)

5.11. Case Study Analysis

5.12. Investment and Funding Scenario

5.13. Regulatory Landscape

5.13.1. Regulatory Bodies, Government Agencies, and Other Organizations

5.13.2. Regulatory Framework

5.14. Porters Five Force Analysis

5.14.1. Threat from New Entrants

5.14.2. Threat of Substitutes

5.14.3. Bargaining Power of Suppliers

5.14.4. Bargaining Power of Buyers

5.14.5. Intensity of Competitive Rivalry

5.15. Key Stakeholders and Buying Criteria

5.15.1. Key Stakeholders in Buying Process

5.15.2. Buying Criteria

5.16. Impact of Artificial Intelligence on AI-Driven Predictive Maintenance Market

6 AI-Driven Predictive Maintenance Market, By Solution

6.1. Introduction

6.2. Integrated Solution

6.3. Standalone Solution

7 AI-Driven Predictive Maintenance Market, By Deployment Mode

7.1. Introduction

7.2. Cloud

7.3. On-premises

8 AI-Driven Predictive Maintenance Market, By Organization Size

8.1. Introduction

8.2. Large Enterprises

8.3. Small and Medium-Sized Enterprises

9 AI-Driven Predictive Maintenance Market, By Technique

9.1. Introduction

9.2. Vibration Analysis

9.3. Infrared Thermography

9.4. Acoustic Monitoring

9.5. Oil Analysis

9.6. Motor Circuit Analysis

9.7. Other Techniques

10 AI-Driven Predictive Maintenance Market, By Industry

10.1. Introduction

10.2. Energy & Utilities

10.3. Oil & Gas

10.4. Food & Beverages

10.5. Automotive & Transportation

10.6. Aerospace

10.7. Manufacturing

10.8. Healthcare

10.9. Telecommunications

10.10. Others

11 AI-Driven Predictive Maintenance Market, By Region

11.1. Introduction

11.2. North America

11.2.1. Macro-Economic Outlook

11.2.2. US

11.2.3. Canada

11.2.4. Mexico

11.3. Europe

11.3.1. Macro-Economic Outlook

11.3.2. Germany

11.3.3. UK

11.3.4. France

11.3.5. Italy

11.3.6. Spain

11.3.7. Netherlands

11.3.8. Switzerland

11.3.9. Rest of Europe

11.4. Asia Pacific

11.4.1. Macro-Economic Outlook

11.4.2. China

11.4.3. Japan

11.4.4. India

11.4.5. South Korea

11.4.6. Australia

11.4.7. Indonesia

11.4.8. Rest of Asia Pacific

11.5. RoW

11.5.1. Macro-Economic Outlook

11.5.2. Middle East

11.5.3. Africa

11.5.4. South America

12 AI-Driven Predictive Maintenance Market, Competitive Landscape

12.1. Introduction

12.2. Key player strategies/right to win

12.3. Revenue Analysis

12.4. Market Share Analysis

12.5. Company Valuation and Financial Metrics

12.6. Brand/Product Comparison

12.7. Company Evaluation Matrix: Key Players, 2024

12.7.1. Stars

12.7.2. Emerging Leaders

12.7.3. Pervasive Players

12.7.4. Participants

12.7.5. Company Footprint: Key Players, 2024

12.8. Company Evaluation Matrix: Startups/SMEs, 2024

12.8.1. Progressive Companies

12.8.2. Responsive Companies

12.8.3. Dynamic Companies

12.8.4. Starting Blocks

12.8.5. Competitive Benchmarking: Startups/SMEs, 2024

12.8.5.1. Detailed List of Key Startups/SMEs

12.8.5.2. Competitive Benchmarking of Key Startups/SMEs

12.9. Competitive Situation and Trends

13 AI-Driven Predictive Maintenance Market, Company Profiles

13.1. Key Players

13.1.1. ABB

13.1.2. Microsoft

13.1.3. SAP SE

13.1.4. Siemens.

13.1.5. Infinite Uptime Inc.

13.1.6. C3.ai, Inc.

13.1.7. AVEVA?Group

13.2. Other Players

14 Appendix

14.1. Discussion Guide

14.2. Knowledge Store: MarketsandMarkets’ Subscription Portal

14.3. Available Customizations

14.4. Related Reports

14.5. Author Details

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Al-Driven Predictive Maintenance Market

Al-Driven Predictive Maintenance Market by Solution (Integrated Solution, Standalone Solution), Deployment Mode (Cloud, On-premises), Technique (Vibration Analysis, Infrared Thermography, Oil Analysis), Organization Size, Industry - Global Forecast to 2030

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