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汽車人工智慧診斷市場預測至2032年：按組件、車輛類型、部署、技術、應用、最終用戶和地區分類的全球分析

Automotive AI Diagnostics Market Forecasts to 2032 - Global Analysis By Component (Diagnostic Software, Diagnostic Equipment and Services), Vehicle Type, Deployment, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的一項研究，預計到 2025 年，全球汽車人工智慧診斷市場規模將達到 69 億美元，到 2032 年將達到 830 億美元，預測期內複合年成長率將達到 42.8%。

汽車人工智慧診斷是指應用人工智慧技術來監測、分析和預測車輛性能和健康狀況。這些系統利用機器學習演算法、感測器數據和高級分析技術來檢測故障、評估零件狀況，並提供車輛運作的即時資訊。透過在潛在問題變得嚴重之前識別它們，人工智慧診斷可以提高安全性、降低維護成本並提升整體效率。這對於配備複雜電子系統、自動駕駛功能和互聯平台的現代車輛尤其重要，它能夠確保預防性維護，並為製造商和消費者帶來最佳化的駕駛體驗。

自動駕駛汽車的進展

自動駕駛技術的進步正以不可阻擋的速度推動汽車人工智慧診斷市場的發展。隨著車輛配備更多感測器、決策能力和先進電子設備，對智慧診斷系統的需求也日益成長。人工智慧工具將成為安全的無聲守護者，持續監控系統健康狀況，並在故障發生前進行預測。由於自動駕駛技術完全依賴完美無瑕的性能，製造商正在採用人工智慧診斷技術來最大限度地降低風險、提高可靠性，並確保自動駕駛行駛更加平穩、安全和可靠。

高昂的實施成本

高昂的實施成本仍然是汽車人工智慧診斷市場的主要限制因素。部署先進的人工智慧系統需要在硬體、軟體和專業人員方面進行大量投資，這使得中小型製造商和車隊營運商難以採用。感測器、雲端平台和機器學習模型的整合增加了成本，而持續的維護進一步推高了營運成本。這些財務障礙減緩了科技的普及速度，並限制了其可及性，尤其是在發展中地區。

車輛複雜性日益增加

隨著現代車輛的複雜性日益增加，感測器、ECU、連接層和自動駕駛功能也隨之增多，人工智慧診斷的潛力也隨之大幅提升。傳統的診斷方法已無法應對現代車輛中海量資料的湧入。人工智慧應運而生，成為至關重要的解讀工具，能夠將紛繁複雜的數據轉化為清晰明了的資訊。製造商越來越依賴預測性洞察來管理複雜的系統、減少停機時間並預防故障。這種日益成長的複雜性正推動人工智慧診斷從「可選」走向「必備」。

整合挑戰

整合挑戰威脅著市場發展勢頭。舊有系統、多樣化的車輛架構和碎片化的標準使得無縫部署舉步維艱。汽車製造商難以將人工智慧平台與現有電子設備整合，導致相容性問題和交付延遲。資料隱私擔憂、網路安全風險以及不一致的通訊協定進一步加劇了這一困境。車隊和原始設備製造商 (OEM) 常常面臨漫長的部署週期和系統適配障礙。缺乏統一的框架，人工智慧診斷無法發揮其真正的潛力，由此產生的差距會減緩其普及速度，並令早期採用者感到沮喪。

新冠疫情的影響：

新冠疫情既為汽車人工智慧診斷帶來了阻礙，也使其發展更加緊迫。供應鏈中斷導致生產延遲，技術升級放緩，尤其是對硬體依賴型解決方案而言。然而，疫情也加速了數位轉型，推動了汽車製造商採用遠端監控、預測性維護和人工智慧驅動的偵測工具，以減少人際接觸。隨著消費者偏好轉向更安全、更可靠的車輛，診斷技術已成為疫情時代策略的核心。

預計在預測期內，深度學習（DL）細分市場將佔據最大的市場佔有率。

預計在預測期內，深度學習 (DL) 領域將佔據最大的市場佔有率，因為它在故障檢測、模式識別和預測分析方面擁有無與倫比的精確度。深度學習模型能夠利用現代車輛產生的大量資料集，並以遠超人類的速度處理感測器資料流，同時還能像人類一樣進行解讀。這使其成為診斷細微電氣問題和輔助自動駕駛安全層的理想選擇。汽車製造商高度重視深度學習能夠隨著車輛行駛里程的增加而不斷學習和改進的能力。其精準性已使其成為先進診斷技術的基礎。

預計在預測期內，車隊營運商細分市場將實現最高的複合年成長率。

由於車隊營運商高度依賴人工智慧診斷來減少停機時間、控制維修成本並延長車輛使用壽命，預計在預測期內，車隊營運商細分市場將實現最高成長率。大規模的車隊會產生大量數據，因此預測性洞察具有巨大的價值。人工智慧可以幫助營運商智慧地規劃維護、預防運作中故障並最佳化資產利用率。隨著物流、共乘、配送網路和租賃公司規模的擴大，它們對即時診斷平台的投資也不斷增加。效率帶來利潤，而人工智慧則是保障車輛行駛安全每時每刻的工具。

佔比最大的地區：

由於智慧運輸解決方案的快速普及和聯網汽車需求的蓬勃發展，亞太地區預計將在預測期內佔據最大的市場佔有率。中國、日本和韓國等國家正競相推出自動駕駛試點計畫、廣泛普及電動車，並推廣智慧型運輸系統（ITS），而這些都需要先進的診斷技術。政府對汽車創新的支持進一步推動了這一發展勢頭。憑藉精通技術的消費者和實力雄厚的汽車製造商，該地區自然有望佔據人工智慧診斷應用的大部分佔有率。

年複合成長率最高的地區：

在預測期內，北美預計將實現最高的複合年成長率，這得益於其強大的AI開發者、自動駕駛公司、汽車創新者和數據分析先驅者的生態系統。該地區對聯網汽車和遠距自動駕駛的大力投入，正推動對預測性診斷系統的強勁需求。以安全為中心的法規，加上車隊營運商的高採用率，正在加速這一趨勢。矽谷在人工智慧領域的領先地位與底特律強大的製造業實力相結合，使北美成為面向未來的診斷技術成長最快的中心。

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目錄

第1章執行摘要

第2章 前言

  • 摘要
  • 相關利益者
  • 調查範圍
  • 調查方法
  • 研究材料

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球汽車人工智慧診斷市場（按組件分類）

  • 診斷軟體
  • 診斷設備
  • 服務

6. 全球汽車人工智慧診斷市場（按車輛類型分類）

  • 搭乘用車
  • 混合動力汽車
  • 商用車輛
  • 電動車（EV）

7. 全球汽車人工智慧診斷市場（以部署方式分類）

  • 本地部署
  • 雲端基礎的

8. 全球汽車人工智慧診斷市場（按技術分類）

  • 機器學習（ML）
  • 電腦視覺
  • 深度學習（DL）
  • 自然語言處理（NLP）

9. 全球汽車人工智慧診斷市場（按應用分類）

  • 車輛健康監測
  • 車載診斷系統（OBD）
  • 預測性維護
  • 遠距離診斷
  • ADAS（進階駕駛輔助系統）
  • 安全與合規

第10章 全球汽車人工智慧診斷市場（按最終用戶分類）

  • 汽車製造商（OEM）
  • 研究所
  • 售後服務服務供應商
  • 車隊營運商

第11章 全球汽車人工智慧診斷市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美國家
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 併購
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第13章：企業概況

  • Robert Bosch GmbH
  • Continental AG
  • Aptiv PLC
  • DENSO Corporation
  • NVIDIA Corporation
  • ZF Friedrichshafen AG
  • Magna International Inc.
  • Valeo SA
  • AVL List GmbH
  • Vector Informatik GmbH
  • Autel Intelligent Technology Corp., Ltd.
  • TEXA SpA
  • Snap-on Incorporated
  • Infineon Technologies AG
  • BorgWarner Inc.
Product Code: SMRC32688

According to Stratistics MRC, the Global Automotive AI Diagnostics Market is accounted for $6.9 billion in 2025 and is expected to reach $83.0 billion by 2032 growing at a CAGR of 42.8% during the forecast period. Automotive AI Diagnostics refers to the application of artificial intelligence technologies in monitoring, analyzing, and predicting the performance and health of vehicles. These systems leverage machine learning algorithms, sensor data, and advanced analytics to detect faults, assess component conditions, and provide real-time insights into vehicle operations. By identifying potential issues before they escalate, AI diagnostics enhance safety, reduce maintenance costs, and improve overall efficiency. They are particularly vital in modern vehicles equipped with complex electronic systems, autonomous driving features, and connected platforms, ensuring proactive maintenance and optimized driving experiences for both manufacturers and consumers.

Market Dynamics:

Driver:

Advancements in Autonomous Vehicles

Advancements in autonomous driving are pushing the Automotive AI Diagnostics market forward with unstoppable force. As vehicles gain more sensors, decision-making capabilities, and electronic sophistication, the need for intelligent diagnostic systems grows. AI tools become the silent guardians of safety, constantly reading system health and predicting failures before they strike. With self-driving tech depending entirely on flawless performance, manufacturers are embracing AI diagnostics to minimize risks, enhance reliability, and ensure every autonomous mile is smoother, safer, and more dependable.

Restraint:

High Implementation Costs

High implementation costs remain a significant restraint in the automotive AI diagnostics market. Deploying advanced AI systems requires substantial investment in hardware, software, and skilled personnel, making adoption challenging for smaller manufacturers and fleet operators. The integration of sensors, cloud platforms, and machine learning models adds to expenses, while ongoing maintenance further increases operational costs. These financial barriers slow widespread adoption, particularly in developing regions, limiting accessibility.

Opportunity:

Growing Vehicle Complexity

As modern vehicles become more complex-packed with sensors, ECUs, connectivity layers, and autonomous features-the opportunity for AI diagnostics expands dramatically. Traditional diagnostic methods can't keep up with the sheer volume of data flowing through today's cars. AI steps in as the necessary interpreter, turning chaos into clarity. Manufacturers are increasingly relying on predictive insights to manage intricate systems, reduce downtime, and prevent breakdowns. Rising complexity becomes the rising tide that lifts AI diagnostics into essential, not optional, territory.

Threat:

Integration Challenges

Integration challenges threaten market momentum as legacy systems, diverse vehicle architectures, and fragmented standards make seamless adoption difficult. Automakers struggle to fuse AI platforms with existing electronics, causing compatibility issues and delays. Data privacy concerns, cybersecurity risks, and inconsistent communication protocols only complicate matters further. Fleet operators and OEMs often face long onboarding periods and system calibration hurdles. Without unified frameworks, AI diagnostics can't unlock their full power, leaving gaps that slow deployment and frustrate early adopters.

Covid-19 Impact:

Covid-19 brought both setbacks and renewed urgency to automotive AI diagnostics. Supply chain disruptions delayed production and slowed technological upgrades, particularly for hardware-dependent solutions. Yet the pandemic accelerated digital transformation, pushing OEMs to adopt remote monitoring, predictive maintenance, and AI-driven inspection tools to reduce physical contact. As consumer preference shifted toward safer, more reliable vehicles, diagnostic technologies became central to post-pandemic strategies.

The deep learning (DL) segment is expected to be the largest during the forecast period

The deep learning (DL) segment is expected to account for the largest market share during the forecast period, because it delivers unmatched accuracy in fault detection, pattern recognition, and predictive analytics. DL models thrive on massive datasets generated by modern vehicles, interpreting sensor streams with near-human intuition but far greater speed. This makes them ideal for diagnosing subtle electrical issues and supporting autonomous driving safety layers. Automakers favor DL for its ability to continuously improve, learning from every mile driven. Its precision cements it as the backbone of advanced diagnostics.

The fleet operators segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the fleet operators segment is predicted to witness the highest growth rate, as they rely heavily on AI diagnostics to reduce downtime, trim repair costs, and extend vehicle lifespan. With large fleets generating enormous data volumes, predictive insights become invaluable. AI helps operators schedule maintenance intelligently, prevent breakdowns during operations, and optimize asset utilization. As logistics, ride-hailing, delivery networks, and rental companies scale, they increasingly invest in real-time diagnostic platforms. Efficiency becomes profit, and AI becomes the tool that preserves every hour on the road.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, due to rapid adoption of smart mobility solutions, and booming demand for connected vehicles. Countries like China, Japan, and South Korea are racing ahead with autonomous driving pilots, EV expansion, and intelligent transportation systems-all of which require sophisticated diagnostics. Government support for automotive innovation amplifies this momentum. With tech-savvy consumers and strong OEM presence, the region naturally takes the lion's share of AI diagnostic deployments.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to its strong ecosystem of AI developers, autonomous driving firms, automotive innovators, and data-analytics pioneers. The region's push toward connected vehicles and long-haul automation fuels high demand for predictive diagnostic systems. Regulatory emphasis on safety, combined with high adoption among fleet operators, accelerates deployment. With Silicon Valley's AI leadership and Detroit's manufacturing strength converging, North America becomes the hotbed where future-ready diagnostic technologies scale quickest.

Key players in the market

Some of the key players in Automotive AI Diagnostics Market include Robert Bosch GmbH, Continental AG, Aptiv PLC, DENSO Corporation, NVIDIA Corporation, ZF Friedrichshafen AG, Magna International Inc., Valeo SA, AVL List GmbH, Vector Informatik GmbH, Autel Intelligent Technology Corp., Ltd., TEXA S.p.A., Snap-on Incorporated, Infineon Technologies AG, and BorgWarner Inc.

Key Developments:

In June 2025, Continental has signed an agreement to sell its drum-brake production and R&D facility in Cairo Montenotte, Italy including around 400 employees to Mutares, allowing Continental to refocus on core technologies.

In January 2025, Aurora, Continental, and NVIDIA have teamed up to deploy autonomous trucks at scale, combining Aurora's self-driving software, Continental's vehicle systems, and NVIDIA's hardware. Their collaboration targets commercial freight transport with high safety, efficiency, and advanced AI-based driving.

Components Covered:

  • Diagnostic Software
  • Diagnostic Equipment
  • Services

Vehicle Types Covered:

  • Passenger Cars
  • Hybrid Vehicles
  • Commercial Vehicles
  • Electric Vehicles (EVs)

Deployments Covered:

  • On-Premises
  • Cloud-Based

Technologies Covered:

  • Machine Learning (ML)
  • Computer Vision
  • Deep Learning (DL)
  • Natural Language Processing (NLP)

Applications Covered:

  • Vehicle Health Monitoring
  • Onboard Diagnostics (OBD)
  • Predictive Maintenance
  • Remote Diagnostics
  • Advanced Driver Assistance Systems (ADAS)
  • Safety & Compliance

End Users Covered:

  • Original Equipment Manufacturers (OEMs)
  • Research Institutions
  • Aftermarket Service Providers
  • Fleet Operators

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Automotive AI Diagnostics Market, By Component

  • 5.1 Introduction
  • 5.2 Diagnostic Software
  • 5.3 Diagnostic Equipment
  • 5.4 Services

6 Global Automotive AI Diagnostics Market, By Vehicle Type

  • 6.1 Introduction
  • 6.2 Passenger Cars
  • 6.3 Hybrid Vehicles
  • 6.4 Commercial Vehicles
  • 6.5 Electric Vehicles (EVs)

7 Global Automotive AI Diagnostics Market, By Deployment

  • 7.1 Introduction
  • 7.2 On-Premises
  • 7.3 Cloud-Based

8 Global Automotive AI Diagnostics Market, By Technology

  • 8.1 Introduction
  • 8.2 Machine Learning (ML)
  • 8.3 Computer Vision
  • 8.4 Deep Learning (DL)
  • 8.5 Natural Language Processing (NLP)

9 Global Automotive AI Diagnostics Market, By Application

  • 9.1 Introduction
  • 9.2 Vehicle Health Monitoring
  • 9.3 Onboard Diagnostics (OBD)
  • 9.4 Predictive Maintenance
  • 9.5 Remote Diagnostics
  • 9.6 Advanced Driver Assistance Systems (ADAS)
  • 9.7 Safety & Compliance

10 Global Automotive AI Diagnostics Market, By End User

  • 10.1 Introduction
  • 10.2 Original Equipment Manufacturers (OEMs)
  • 10.3 Research Institutions
  • 10.4 Aftermarket Service Providers
  • 10.5 Fleet Operators

11 Global Automotive AI Diagnostics Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Robert Bosch GmbH
  • 13.2 Continental AG
  • 13.3 Aptiv PLC
  • 13.4 DENSO Corporation
  • 13.5 NVIDIA Corporation
  • 13.6 ZF Friedrichshafen AG
  • 13.7 Magna International Inc.
  • 13.8 Valeo SA
  • 13.9 AVL List GmbH
  • 13.10 Vector Informatik GmbH
  • 13.11 Autel Intelligent Technology Corp., Ltd.
  • 13.12 TEXA S.p.A.
  • 13.13 Snap-on Incorporated
  • 13.14 Infineon Technologies AG
  • 13.15 BorgWarner Inc.

List of Tables

  • Table 1 Global Automotive AI Diagnostics Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Automotive AI Diagnostics Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Automotive AI Diagnostics Market Outlook, By Diagnostic Software (2024-2032) ($MN)
  • Table 4 Global Automotive AI Diagnostics Market Outlook, By Diagnostic Equipment (2024-2032) ($MN)
  • Table 5 Global Automotive AI Diagnostics Market Outlook, By Services (2024-2032) ($MN)
  • Table 6 Global Automotive AI Diagnostics Market Outlook, By Vehicle Type (2024-2032) ($MN)
  • Table 7 Global Automotive AI Diagnostics Market Outlook, By Passenger Cars (2024-2032) ($MN)
  • Table 8 Global Automotive AI Diagnostics Market Outlook, By Hybrid Vehicles (2024-2032) ($MN)
  • Table 9 Global Automotive AI Diagnostics Market Outlook, By Commercial Vehicles (2024-2032) ($MN)
  • Table 10 Global Automotive AI Diagnostics Market Outlook, By Electric Vehicles (EVs) (2024-2032) ($MN)
  • Table 11 Global Automotive AI Diagnostics Market Outlook, By Deployment (2024-2032) ($MN)
  • Table 12 Global Automotive AI Diagnostics Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 13 Global Automotive AI Diagnostics Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 14 Global Automotive AI Diagnostics Market Outlook, By Technology (2024-2032) ($MN)
  • Table 15 Global Automotive AI Diagnostics Market Outlook, By Machine Learning (ML) (2024-2032) ($MN)
  • Table 16 Global Automotive AI Diagnostics Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 17 Global Automotive AI Diagnostics Market Outlook, By Deep Learning (DL) (2024-2032) ($MN)
  • Table 18 Global Automotive AI Diagnostics Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 19 Global Automotive AI Diagnostics Market Outlook, By Application (2024-2032) ($MN)
  • Table 20 Global Automotive AI Diagnostics Market Outlook, By Vehicle Health Monitoring (2024-2032) ($MN)
  • Table 21 Global Automotive AI Diagnostics Market Outlook, By Onboard Diagnostics (OBD) (2024-2032) ($MN)
  • Table 22 Global Automotive AI Diagnostics Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 23 Global Automotive AI Diagnostics Market Outlook, By Remote Diagnostics (2024-2032) ($MN)
  • Table 24 Global Automotive AI Diagnostics Market Outlook, By Advanced Driver Assistance Systems (ADAS) (2024-2032) ($MN)
  • Table 25 Global Automotive AI Diagnostics Market Outlook, By Safety & Compliance (2024-2032) ($MN)
  • Table 26 Global Automotive AI Diagnostics Market Outlook, By End User (2024-2032) ($MN)
  • Table 27 Global Automotive AI Diagnostics Market Outlook, By Original Equipment Manufacturers (OEMs) (2024-2032) ($MN)
  • Table 28 Global Automotive AI Diagnostics Market Outlook, By Research Institutions (2024-2032) ($MN)
  • Table 29 Global Automotive AI Diagnostics Market Outlook, By Aftermarket Service Providers (2024-2032) ($MN)
  • Table 30 Global Automotive AI Diagnostics Market Outlook, By Fleet Operators (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.