人工智慧及其在商用车市场的应用，全球（2024-2029）

本报告检视了全球商用车市场，并分析了影响商用车产业的当前趋势和市场力量、与商用车相关的人工智慧技术的进步，以及有关主要企业及其战略倡议的资讯。

人工智慧对商用车产业三大战略要务的影响

变革性大趋势

• 原因：从车辆设计製造到销售、营运和安全，人工智慧正在彻底改变商用车产业，为整个生态系统创造价值。人工智慧对于电动车和自动驾驶汽车的无缝整合至关重要，而这项变革将引领产业走向永续的高效运作。
• 弗若斯特的观点：人工智慧将在商用车生命週期的关键转型趋势中发挥关键作用。随着数据生成呈指数级增长，人工智慧对于提高效率和建立所有营运环节的标准化至关重要。

颠覆性技术

• 原因：人工智慧赋能的车辆设计速度更快、效率更高、外观更美观，正在革新商用车产业，协助打造个人化、高效节能的汽车。车载资讯服务和物流是人工智慧推动快速变革的关键领域，分别透过整合预测性维护和货物视觉化，改变市场动态以及车队管理者与其车队之间的互动方式。
• 弗罗斯特的观点：人工智慧对于革新车队管理和营运方式至关重要。产业需求不断增长，包括更快的交付速度、更有效率的新设计、更高的安全性以及个人化的车内体验。人工智慧是满足这些需求的关键。此外，人工智慧正在革新维护和远端资讯处理技术，有助于最大限度地降低总营运成本。

压缩客户价值链

• 原因：在商用车领域，人工智慧透过降低维护成本和提高营运效率，缩短了客户价值链。汽车人工智慧技术透过语音助理和高级驾驶辅助系统（ADAS）改善驾驶体验，同时透过减少事故来盈利。
• 弗若斯特的观点：随着每秒产生数TerabyteTB的数据，人工智慧强大的处理能力将简化传统决策流程的各个阶段，从而实现更快、更有效的决策并创造价值。人工智慧将继续透过提高营运效率和降低总营运成本，积极推动价值链的压缩。

成长驱动因素

• 车载资讯系统与联网汽车的发展
• 不断扩大的物流和电子商务领域
• 对效率的需求日益增长
• 安全性提高
• 竞争优势

成长抑制因素

• 监管限制
• 假阳性
• 资料隐私和安全问题
• 前期成本高
• 用户验收

目录

调查范围

• 调查范围
• 分割

人工智慧在电脑视觉产业的3大战略要务

• 为什么经济成长变得越来越困难？
• The Strategic Imperative 8
• 人工智慧对电脑视觉产业三大战略要务的影响

目的、目标、范围

• 本研究的目的、目标和要回答的主要问题
• 调查方法

成长环境：了解人工智慧及其在电脑科学的应用

• 人工智慧：一个广义的定义
• 人工智慧：技术分类
• 影响人工智慧在电脑视觉产业应用的因素
• 人工智慧对电脑视觉生态系统的影响
• 在主要车队服务中部署人工智慧
• 电脑辅助设计中人工智慧服务的演变
• 人工智慧Start-Ups资金筹措排名

成长环境：生态系、主要经营模式、案例研究

• 人工智慧在电脑视觉生命週期中的应用案例
• 人工智慧在电脑视觉生命週期各阶段的应用
• 竞争环境
• 主要竞争对手
• 生态系统 1：供应链解决方案 - 人工智慧应用概述
• 案例研究：FourKites，一家领先的货物可视性公司
• 生态系统 2：软体设计 - 人工智慧应用概述
• 案例研究：达梭系统，一家领先的设计软体公司
• 生态系统 3：远端资讯处理—人工智慧应用概述
• 案例研究：Samsara，一家领先的远端资讯处理和故障预测公司

推动人工智慧在电脑视觉领域应用的关键趋势和案例研究

• 推动人工智慧在电脑视觉领域应用的关键趋势
• 趋势一：自动驾驶
• 趋势二：情绪智商
• 趋势三：失败预测
• 趋势四：自动化工作指导

人工智慧在电脑视觉产业中的成长要素

• 成长指标
• 成长驱动因素
• 成长抑制因素
• 预测考量
• 电脑视觉产业的AI收入管道
• 经营模式及收入管道映射
• 电脑视觉产业人工智慧总收入估计值
• 按关键电脑视觉应用场景分類的订阅式人工智慧收入
• 按地区分類的订阅式人工智慧收入明细
• 收入预测
• 预测分析
• 价格趋势

人工智慧在全部区域的应用

• 人工智慧应用区域概况
• 影响人工智慧成长的区域因素
• 区域人工智慧采用率评分
• 电脑视觉产业人工智慧应用主要区域比较

成长机会：人工智慧在履历行业的应用

• 发展机会 1：高品质的车内体验
• 成长机会 2：自动化车队管理运营
• 成长机会 3：自动配送与驾驶辅助

附录：后续步骤

AI is Driving Transformational Growth in Commercial Vehicles

This study examines the development prospects that artificial intelligence (AI) offers the commercial vehicle (CV) industry, focusing on both the revolutionary potential of AI and the difficulties businesses face in fostering growth, including complicated regulations, high capital expenditure, and challenges in incorporating new technology into pre-existing systems as the industry becomes more competitive. Owing to these obstacles, businesses are challenged to scale and maintain growth. In such a scenario, AI is a potential facilitator, providing solutions to boost safety, optimize operations, and improve customer experiences-all of which eventually promote expansion in an industry that is changing quickly.

The study starts by outlining AI in terms of its use throughout the CV life cycle. AI is defined, and several subsets of technologies are examined, including robotics, machine learning, and natural language processing, all of which can be applied in CVs. These technologies improve the efficiency and performance of commercial fleets across several critical fleet activities, including autonomous driving, ADAS and driver behavior, predictive maintenance, and real-time decision-making. From enhancing car design to revolutionizing supply chain operations, AI's influence spans the entire CV life cycle, highlighting its widespread applicability and promise in this field.

The study also discusses how AI is used in design, sales, operations, and in-vehicle features. Each life cycle stage's key ecosystems are examined, and a case study is used to show how AI is impacting the industry. The study includes real-world examples of how businesses are successfully incorporating AI into their operations for each ecosystem and its key fleet applications. Leaders in AI adoption include Dassault Systemes for its ongoing innovation in software-generated designs, FourKites, which uses AI to track vehicle data and monitor fleet performance, and Samsara, which employs AI to monitor fleet performance. These case studies highlight the advantages AI offers CV operations, including increased productivity, reduced expenses, and better service.

The study then explores the major global trends of AI in the CV industry, including work order automation, prognostics, emotional intelligence, and autonomous driving. While emotional intelligence improves user-vehicle connections and makes cars safer and more proactive, autonomous driving technology is predicted to transform transportation by decreasing human intervention and boosting efficiency. Work order automation improves overall efficiency by streamlining operations and decreasing administrative burdens, while prognostics-the capacity to anticipate vehicle breakdowns before they happen-helps businesses save maintenance costs.

With an emphasis on the major business models propelling AI adoption, the study also discusses the competitive landscape in the AI-driven CV space. The primary business models for the CV industry to acquire revenue traction are hardware-integrated solutions, software-as-a-service (SaaS) models, and subscription-based services. In addition, the business models are dissected ecosystem- and fleet-operation-wise, and an AI-based revenue estimate for the entire CV industry is calculated. Furthermore, the study compares global regions using criteria that have a significant impact on the regional development of AI and important areas of AI's rapid expansion in the CV industry.

The study concludes by highlighting several significant potential prospects in the AI-driven CV space. As AI develops, it will play a crucial role in fostering innovation and expansion in the CV industry and assisting businesses in streamlining processes, cutting expenses, and maintaining their competitiveness in a world that is becoming increasingly automated. By adopting AI, the CV industry can open new growth prospects and revolutionize the international transportation of products and services.

Scope

• Market Dynamics
  • Analysis of current trends and market forces impacting the commercial vehicle sector.
• Technology Trends
  • Examination of advancements in AI technologies relevant to commercial vehicles.
• Competitive Landscape
  • Overview of key players and their strategic initiatives.

The Impact of the Top 3 Strategic Imperatives of AI in the CV Industry

Transformative Megatrends

• Why: From vehicle design and manufacturing to sales, operations, and safety, AI is revolutionizing the CV industry and generating value throughout the ecosystem. AI is essential for the seamless integration of electric and autonomous vehicles, leading to a shift that drives the sector toward sustainable efficiency.
• Frost Perspective: AI will play a key role in major transformative trends across the entire life cycle of CVs. With exponential data generation, AI is crucial for enhancing efficiency and establishing standardization across all operations.

Disruptive Technologies

• Why: The CV industry is being disrupted by faster, more efficient, and aesthetically pleasing vehicle designs enabled by AI, facilitating the production of personalized and efficient automobiles. Telematics and logistics are key areas where AI is driving rapid disruption by integrating prognostics and freight visibility, respectively, altering market dynamics and the interaction between fleet operators and their fleets.
• Frost Perspective: AI will be pivotal in disrupting conventional vehicle management and operational practices. Industry demands are continually escalating, characterized by shorter delivery times, new and efficient designs, safer vehicles, and personalized cabin experiences. AI will be vital in addressing these demands. In addition, maintenance and telematics are experiencing AI disruptions, where it is being leveraged to minimize total operational costs.

Customer Value Chain Compression

• Why: In CVs, AI shortens the customer value chain by simultaneously reducing maintenance costs and enhancing operational efficiency. In-cabin AI features improve the overall driving experience with voice assistants and ADAS, while also reducing accidents, leading to increased profitability.
• Frost Perspective: With millions of terabytes (TB) of data generated every second, AI, with its high processing power, cuts through multiple layers of conventional decision-making with faster and more efficient decisions, generating value. AI is and will continue to actively contribute to value chain compression by minimizing total operational costs through increased operational efficiency.

Competitive Environment

• Number of Competitors
  • >25
• Competitive Factors
  • Technology, accuracy, partnerships, cost, performance, support, reliability, ease of integration, customer relationships
• Key End-user Industry Verticals
  • CVs, passenger vehicles (PVs), two wheelers (2Ws)
• Leading Competitors
  • Amazon, Apple, Baidu, Nvidia, Meta, Microsoft, IBM, Uber
• Other Notable Competitors
  • Adobe, Dell, Intel, AMD, Salesforce
• Distribution Structure
  • Technology companies, data science companies, OEMs, fleet managers
• Notable Mergers and Acquisitions
  • Microsoft acquired OpenAI; Google acquired Waymo

Growth Drivers

• Growth of telematics and connected vehicles
• Growing logistics and eCommerce sectors
• Increasing demand for efficiency
• Safety improvements
• Competitive advantages

Growth Restraints

• Regulatory restrictions
• False positives
• Data privacy and security concerns
• High initial costs
• User acceptance

Key Competitors

• Siemens
• Dasault Systems
• Ulpath
• UBTech
• Autodesk
• Blue Prism
• Verizon
• Samsara
• Tusimple
• Aurora
• Geotab
• Pretekt
• Pitstop
• Project 44
• Transplace
• Four Kites
• Amazon, Meta
• Salesforce
• Imaginovate
• Light
• Pearl Auto
• Phantom
• In-cabing assistance
• Safety & ADAS
• Marketing & dynamic pricing
• Robotics automation
• Design software
• Telematic

Table of Contents

Research Scope

• Scope of the Study
• Segmentation

Top 3 Strategic Imperatives of AI in the CV Industry

• Why Is It Increasingly Difficult to Grow?
• The Strategic Imperative 8
• The Impact of the Top 3 Strategic Imperatives of AI in the CV Industry

Aim, Objectives, and Scope

• Aim, Objectives, and Key Questions the Study Answers
• Research Methodology

Growth Environment: Understanding AI and its Applications in CVs

• AI: A Broad Definition
• AI: Technology Classification
• Factors Influencing AI in the CV Industry
• AI Impact on the CV Ecosystem
• AI Deployment in Key Fleet Services
• Evolution of AI Services in CVs
• AI Start-Ups Ranked by Funding

Growth Environment: Ecosystem, Key Business Models, and Case Studies

• AI Use Cases Throughout the CV Life Cycle
• AI Applications in Each Stage of the CV Life Cycle
• Competitive Environment
• Key Competitors
• Ecosystem 1: Supply Chain Solutions-Overview of AI Penetration
• Case Study: FourKites Major Freight Visibility Participant
• Ecosystem 2: Design Software-Overview of AI Penetration
• Case Study: Dassault Systems Major Design Software Company
• Ecosystem 3: Telematics-Overview of AI Penetration
• Case Study: Samsara Major Telematics and Prognostics Company

Key Trends Driving AI in CVs, and Case Studies

• Key Trends Driving AI in CVs
• Trend 1: Autonomous Driving
• Trend 2: Emotional Intelligence
• Trend 3: Prognostics
• Trend 4: Work Order Automation

Growth Generator for AI in the CV Industry

• Growth Metrics
• Growth Drivers
• Growth Restraints
• Forecast Considerations
• Revenue Channels for AI in the CV Industry
• Business Models Mapped Across Revenue Channels
• Estimated Total AI Revenue of the CV Industry
• Subscription-Based AI Revenue by Key CV Applications
• Subscription-Based AI Revenue Breakdown by Regions
• Revenue Forecast
• Forecast Analysis
• Pricing Trends

Regionwide Landscape of AI Adoption

• Regional Overview of AI Adoption
• Regional Factors Influencing AI Growth
• Regional AI Adoption Score
• Comparison of Key Regions in AI Adoption in the CV Industry

Growth Opportunity Universe: AI in the CV Industry

• Growth Opportunity 1: High-Quality In-Vehicle Experiences
• Growth Opportunity 2: Automated Fleet Management Operations
• Growth Opportunity 3: Autonomous Deliveries and Assisted Driving

Appendix & Next Steps

• Benefits and Impacts of Growth Opportunities
• Next Steps
• List of Exhibits
• Legal Disclaimer