The global market for AI-Assisted Diagnosis was estimated to be worth US$ 25100 million in 2024 and is forecast to a readjusted size of US$ 64565 million by 2031 with a CAGR of 16.0% during the forecast period 2025-2031.
AI-Assisted Diagnosis refers to the use of artificial intelligence technologies to detect, predict, and diagnose faults in industrial equipment. It integrates machine learning, deep learning, data mining, and sensor technologies to collect real-time data on equipment performance, analyze its condition, and identify potential faults using intelligent algorithms. The primary goal of this technology is to monitor the health status of equipment, detect potential issues in advance, reduce downtime, optimize maintenance schedules, and improve production efficiency.
AI-Assisted Diagnosis is widely applied in various sectors, particularly in industries such as manufacturing, energy, transportation, and aerospace. For equipment that requires high precision and reliability, such as wind turbines, aircraft engines, and robots, AI diagnostic technologies can monitor real-time data on vibration, temperature, pressure, and other parameters to predict potential faults and provide maintenance recommendations. This helps to avoid unexpected failures and extends the lifespan of equipment. The system typically includes sensors, data acquisition devices, data transmission systems, and diagnostic algorithm modules, generating real-time health reports and providing intelligent alerts.
As AI technologies continue to evolve, the accuracy and scope of AI-Assisted Diagnosis are expanding. More and more companies are adopting this technology to achieve intelligent and automated equipment maintenance and management, thereby enhancing the stability and efficiency of production lines.
The AI-Assisted Diagnosis market is rapidly growing, primarily driven by advancements in industrial automation, smart manufacturing, and Internet of Things (IoT) technologies. The increasing demand for efficiency and reliability in equipment maintenance across industries such as manufacturing, energy, and transportation has led to the widespread adoption of AI technologies for fault diagnosis. This is especially true for industries that require high-precision equipment operation, such as aerospace, energy, and automotive manufacturing, where AI fault diagnosis technologies help reduce human intervention and minimize downtime.
Key driving factors for the market include: First, the widespread adoption of the Industrial Internet of Things (IIoT) has enabled more equipment to collect real-time operational data, providing abundant data sources for AI diagnostics. Second, the advancement of smart manufacturing and automated production lines has made AI fault diagnosis systems essential for improving production efficiency and equipment management. Additionally, continuous progress in AI algorithms and computational power has significantly enhanced the accuracy and real-time performance of equipment fault diagnosis.
However, the market faces some challenges and risks. First, implementing AI-Assisted Diagnosis requires a large amount of high-quality data, and the acquisition, transmission, and storage of such data present technical and security challenges. Second, the complexity and diversity of equipment faults require AI algorithms to be highly adaptable, necessitating customized solutions for different equipment and operational conditions. Finally, the training of maintenance personnel and their acceptance of the technology are crucial factors for widespread adoption.
Regarding market concentration, large tech companies such as Siemens, GE, and ABB have made significant strides in the field and have expanded their market share through acquisitions and partnerships. As the technology matures, more innovative companies are expected to emerge. In terms of downstream demand, industries such as manufacturing, energy, and high-end equipment production are the primary drivers of AI-Assisted Diagnosis, particularly those sectors with critical equipment operation and high levels of automation, which will drive widespread adoption of this technology.
This report aims to provide a comprehensive presentation of the global market for AI-Assisted Diagnosis, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of AI-Assisted Diagnosis by region & country, by Type, and by Application.
The AI-Assisted Diagnosis market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding AI-Assisted Diagnosis.
Market Segmentation
By Company
- Alibaba
- Alphabet
- Cisco
- DELL
- GE Digital
- IBM
- Intel
- MECHANICA AI BV
- Microsoft
- Oracle
- PSI Software AG
- Rockwell Automation
- SANY Heavy Industry
- SAP
- SAS
- Siemens
- Uptake Technologies Inc
- Schneider Electric
- Honeywell
- Bosch
Segment by Type
Segment by Application
- Visualization Analysis
- Self Diagnoses
- Predictive Maintenance
- Others
By Region
- North America
- Asia-Pacific
- China
- Japan
- South Korea
- Southeast Asia
- India
- Australia
- Rest of Asia-Pacific
- Europe
- Germany
- France
- U.K.
- Italy
- Netherlands
- Nordic Countries
- Rest of Europe
- Latin America
- Mexico
- Brazil
- Rest of Latin America
- Middle East & Africa
- Turkey
- Saudi Arabia
- UAE
- Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of AI-Assisted Diagnosis company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of AI-Assisted Diagnosis in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of AI-Assisted Diagnosis in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.
Table of Contents
1 Market Overview
- 1.1 AI-Assisted Diagnosis Product Introduction
- 1.2 Global AI-Assisted Diagnosis Market Size Forecast (2020-2031)
- 1.3 AI-Assisted Diagnosis Market Trends & Drivers
- 1.3.1 AI-Assisted Diagnosis Industry Trends
- 1.3.2 AI-Assisted Diagnosis Market Drivers & Opportunity
- 1.3.3 AI-Assisted Diagnosis Market Challenges
- 1.3.4 AI-Assisted Diagnosis Market Restraints
- 1.4 Assumptions and Limitations
- 1.5 Study Objectives
- 1.6 Years Considered
2 Competitive Analysis by Company
- 2.1 Global AI-Assisted Diagnosis Players Revenue Ranking (2024)
- 2.2 Global AI-Assisted Diagnosis Revenue by Company (2020-2025)
- 2.3 Key Companies AI-Assisted Diagnosis Manufacturing Base Distribution and Headquarters
- 2.4 Key Companies AI-Assisted Diagnosis Product Offered
- 2.5 Key Companies Time to Begin Mass Production of AI-Assisted Diagnosis
- 2.6 AI-Assisted Diagnosis Market Competitive Analysis
- 2.6.1 AI-Assisted Diagnosis Market Concentration Rate (2020-2025)
- 2.6.2 Global 5 and 10 Largest Companies by AI-Assisted Diagnosis Revenue in 2024
- 2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in AI-Assisted Diagnosis as of 2024)
- 2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
- 3.1 Introduction by Type
- 3.1.1 Hardware
- 3.1.2 Software
- 3.2 Global AI-Assisted Diagnosis Sales Value by Type
- 3.2.1 Global AI-Assisted Diagnosis Sales Value by Type (2020 VS 2024 VS 2031)
- 3.2.2 Global AI-Assisted Diagnosis Sales Value, by Type (2020-2031)
- 3.2.3 Global AI-Assisted Diagnosis Sales Value, by Type (%) (2020-2031)
4 Segmentation by Application
- 4.1 Introduction by Application
- 4.1.1 Visualization Analysis
- 4.1.2 Self Diagnoses
- 4.1.3 Predictive Maintenance
- 4.1.4 Others
- 4.2 Global AI-Assisted Diagnosis Sales Value by Application
- 4.2.1 Global AI-Assisted Diagnosis Sales Value by Application (2020 VS 2024 VS 2031)
- 4.2.2 Global AI-Assisted Diagnosis Sales Value, by Application (2020-2031)
- 4.2.3 Global AI-Assisted Diagnosis Sales Value, by Application (%) (2020-2031)
5 Segmentation by Region
- 5.1 Global AI-Assisted Diagnosis Sales Value by Region
- 5.1.1 Global AI-Assisted Diagnosis Sales Value by Region: 2020 VS 2024 VS 2031
- 5.1.2 Global AI-Assisted Diagnosis Sales Value by Region (2020-2025)
- 5.1.3 Global AI-Assisted Diagnosis Sales Value by Region (2026-2031)
- 5.1.4 Global AI-Assisted Diagnosis Sales Value by Region (%), (2020-2031)
- 5.2 North America
- 5.2.1 North America AI-Assisted Diagnosis Sales Value, 2020-2031
- 5.2.2 North America AI-Assisted Diagnosis Sales Value by Country (%), 2024 VS 2031
- 5.3 Europe
- 5.3.1 Europe AI-Assisted Diagnosis Sales Value, 2020-2031
- 5.3.2 Europe AI-Assisted Diagnosis Sales Value by Country (%), 2024 VS 2031
- 5.4 Asia Pacific
- 5.4.1 Asia Pacific AI-Assisted Diagnosis Sales Value, 2020-2031
- 5.4.2 Asia Pacific AI-Assisted Diagnosis Sales Value by Region (%), 2024 VS 2031
- 5.5 South America
- 5.5.1 South America AI-Assisted Diagnosis Sales Value, 2020-2031
- 5.5.2 South America AI-Assisted Diagnosis Sales Value by Country (%), 2024 VS 2031
- 5.6 Middle East & Africa
- 5.6.1 Middle East & Africa AI-Assisted Diagnosis Sales Value, 2020-2031
- 5.6.2 Middle East & Africa AI-Assisted Diagnosis Sales Value by Country (%), 2024 VS 2031
6 Segmentation by Key Countries/Regions
- 6.1 Key Countries/Regions AI-Assisted Diagnosis Sales Value Growth Trends, 2020 VS 2024 VS 2031
- 6.2 Key Countries/Regions AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.3 United States
- 6.3.1 United States AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.3.2 United States AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.3.3 United States AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
- 6.4 Europe
- 6.4.1 Europe AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.4.2 Europe AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.4.3 Europe AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
- 6.5 China
- 6.5.1 China AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.5.2 China AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.5.3 China AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
- 6.6 Japan
- 6.6.1 Japan AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.6.2 Japan AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.6.3 Japan AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
- 6.7 South Korea
- 6.7.1 South Korea AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.7.2 South Korea AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.7.3 South Korea AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
- 6.8 Southeast Asia
- 6.8.1 Southeast Asia AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.8.2 Southeast Asia AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.8.3 Southeast Asia AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
- 6.9 India
- 6.9.1 India AI-Assisted Diagnosis Sales Value, 2020-2031
- 6.9.2 India AI-Assisted Diagnosis Sales Value by Type (%), 2024 VS 2031
- 6.9.3 India AI-Assisted Diagnosis Sales Value by Application, 2024 VS 2031
7 Company Profiles
- 7.1 Alibaba
- 7.1.1 Alibaba Profile
- 7.1.2 Alibaba Main Business
- 7.1.3 Alibaba AI-Assisted Diagnosis Products, Services and Solutions
- 7.1.4 Alibaba AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.1.5 Alibaba Recent Developments
- 7.2 Alphabet
- 7.2.1 Alphabet Profile
- 7.2.2 Alphabet Main Business
- 7.2.3 Alphabet AI-Assisted Diagnosis Products, Services and Solutions
- 7.2.4 Alphabet AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.2.5 Alphabet Recent Developments
- 7.3 Cisco
- 7.3.1 Cisco Profile
- 7.3.2 Cisco Main Business
- 7.3.3 Cisco AI-Assisted Diagnosis Products, Services and Solutions
- 7.3.4 Cisco AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.3.5 Cisco Recent Developments
- 7.4 DELL
- 7.4.1 DELL Profile
- 7.4.2 DELL Main Business
- 7.4.3 DELL AI-Assisted Diagnosis Products, Services and Solutions
- 7.4.4 DELL AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.4.5 DELL Recent Developments
- 7.5 GE Digital
- 7.5.1 GE Digital Profile
- 7.5.2 GE Digital Main Business
- 7.5.3 GE Digital AI-Assisted Diagnosis Products, Services and Solutions
- 7.5.4 GE Digital AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.5.5 GE Digital Recent Developments
- 7.6 IBM
- 7.6.1 IBM Profile
- 7.6.2 IBM Main Business
- 7.6.3 IBM AI-Assisted Diagnosis Products, Services and Solutions
- 7.6.4 IBM AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.6.5 IBM Recent Developments
- 7.7 Intel
- 7.7.1 Intel Profile
- 7.7.2 Intel Main Business
- 7.7.3 Intel AI-Assisted Diagnosis Products, Services and Solutions
- 7.7.4 Intel AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.7.5 Intel Recent Developments
- 7.8 MECHANICA AI BV
- 7.8.1 MECHANICA AI BV Profile
- 7.8.2 MECHANICA AI BV Main Business
- 7.8.3 MECHANICA AI BV AI-Assisted Diagnosis Products, Services and Solutions
- 7.8.4 MECHANICA AI BV AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.8.5 MECHANICA AI BV Recent Developments
- 7.9 Microsoft
- 7.9.1 Microsoft Profile
- 7.9.2 Microsoft Main Business
- 7.9.3 Microsoft AI-Assisted Diagnosis Products, Services and Solutions
- 7.9.4 Microsoft AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.9.5 Microsoft Recent Developments
- 7.10 Oracle
- 7.10.1 Oracle Profile
- 7.10.2 Oracle Main Business
- 7.10.3 Oracle AI-Assisted Diagnosis Products, Services and Solutions
- 7.10.4 Oracle AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.10.5 Oracle Recent Developments
- 7.11 PSI Software AG
- 7.11.1 PSI Software AG Profile
- 7.11.2 PSI Software AG Main Business
- 7.11.3 PSI Software AG AI-Assisted Diagnosis Products, Services and Solutions
- 7.11.4 PSI Software AG AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.11.5 PSI Software AG Recent Developments
- 7.12 Rockwell Automation
- 7.12.1 Rockwell Automation Profile
- 7.12.2 Rockwell Automation Main Business
- 7.12.3 Rockwell Automation AI-Assisted Diagnosis Products, Services and Solutions
- 7.12.4 Rockwell Automation AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.12.5 Rockwell Automation Recent Developments
- 7.13 SANY Heavy Industry
- 7.13.1 SANY Heavy Industry Profile
- 7.13.2 SANY Heavy Industry Main Business
- 7.13.3 SANY Heavy Industry AI-Assisted Diagnosis Products, Services and Solutions
- 7.13.4 SANY Heavy Industry AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.13.5 SANY Heavy Industry Recent Developments
- 7.14 SAP
- 7.14.1 SAP Profile
- 7.14.2 SAP Main Business
- 7.14.3 SAP AI-Assisted Diagnosis Products, Services and Solutions
- 7.14.4 SAP AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.14.5 SAP Recent Developments
- 7.15 SAS
- 7.15.1 SAS Profile
- 7.15.2 SAS Main Business
- 7.15.3 SAS AI-Assisted Diagnosis Products, Services and Solutions
- 7.15.4 SAS AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.15.5 SAS Recent Developments
- 7.16 Siemens
- 7.16.1 Siemens Profile
- 7.16.2 Siemens Main Business
- 7.16.3 Siemens AI-Assisted Diagnosis Products, Services and Solutions
- 7.16.4 Siemens AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.16.5 Siemens Recent Developments
- 7.17 Uptake Technologies Inc
- 7.17.1 Uptake Technologies Inc Profile
- 7.17.2 Uptake Technologies Inc Main Business
- 7.17.3 Uptake Technologies Inc AI-Assisted Diagnosis Products, Services and Solutions
- 7.17.4 Uptake Technologies Inc AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.17.5 Uptake Technologies Inc Recent Developments
- 7.18 Schneider Electric
- 7.18.1 Schneider Electric Profile
- 7.18.2 Schneider Electric Main Business
- 7.18.3 Schneider Electric AI-Assisted Diagnosis Products, Services and Solutions
- 7.18.4 Schneider Electric AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.18.5 Schneider Electric Recent Developments
- 7.19 Honeywell
- 7.19.1 Honeywell Profile
- 7.19.2 Honeywell Main Business
- 7.19.3 Honeywell AI-Assisted Diagnosis Products, Services and Solutions
- 7.19.4 Honeywell AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.19.5 Honeywell Recent Developments
- 7.20 Bosch
- 7.20.1 Bosch Profile
- 7.20.2 Bosch Main Business
- 7.20.3 Bosch AI-Assisted Diagnosis Products, Services and Solutions
- 7.20.4 Bosch AI-Assisted Diagnosis Revenue (US$ Million) & (2020-2025)
- 7.20.5 Bosch Recent Developments
8 Industry Chain Analysis
- 8.1 AI-Assisted Diagnosis Industrial Chain
- 8.2 AI-Assisted Diagnosis Upstream Analysis
- 8.2.1 Key Raw Materials
- 8.2.2 Raw Materials Key Suppliers
- 8.2.3 Manufacturing Cost Structure
- 8.3 Midstream Analysis
- 8.4 Downstream Analysis (Customers Analysis)
- 8.5 Sales Model and Sales Channels
- 8.5.1 AI-Assisted Diagnosis Sales Model
- 8.5.2 Sales Channel
- 8.5.3 AI-Assisted Diagnosis Distributors
9 Research Findings and Conclusion
10 Appendix
- 10.1 Research Methodology
- 10.1.1 Methodology/Research Approach
- 10.1.1.1 Research Programs/Design
- 10.1.1.2 Market Size Estimation
- 10.1.1.3 Market Breakdown and Data Triangulation
- 10.1.2 Data Source
- 10.1.2.1 Secondary Sources
- 10.1.2.2 Primary Sources
- 10.2 Author Details
- 10.3 Disclaimer