生成式人工智慧 (GenAI) 及其在汽车领域的应用案例的策略性洞察

生成式人工智慧将在未来十年颠覆汽车价值链

生成式人工智慧 (GenAI) 持续影响着包括汽车在内的各行各业。未来十年，GenAI 预计将对汽车价值链产生重大影响，提高效率和生产力，减少废弃物。在供应链中，它将有助于优化库存和需求预测；在产品开发中，它将有助于产生设计理念，加速原型设计和测试，并缩短产品上市时间；在製造中，它将有助于消除组装上的瓶颈，并为生产工程师提供实时洞察，以便他们做出明智的决策；在零售中，它将为经销商提供与潜在客户的十年，并实现与潜在客户的类人互动；驱动的车载语音助理将成为一项标准功能；在汽车生命週期之外，GenAI 还将为自动驾驶汽车的开发和营运做出重大贡献；未来十年，将涌现出一批专注于自动驾驶汽车解决方案的 GenAIStart-Ups，推动创新并加速自动驾驶汽车的发展。 GenAI 将透过协助简化车队管理、乘车预订、定价和路线规划来支援共享出行。在物流领域，它在选择最佳车辆、根据即时交通数据规划路线、客户支援功能以及企业的其他各种功能（包括财务、人力资源和行销）中发挥着至关重要的作用。

目录

分析范围

GenAI 在汽车领域的成长引擎

• 成长动力
• 成长抑制因素

GenAI概述

• 组织采用 GenAI 的主要原因
• GenAI 与传统 AI
• GenAI 汽车生态系统－关键相关利益者
• 按应用程式选择 GenAI 工具
• 最受欢迎的 GenAI 工具
• IT 决策者对 GenAI 的看法
• 挑战－组织对 GenAI 的担忧
• 主要地区新兴人工智慧法规
• GenAI 概述 – 要点

供应链中的 GenAI

• GenAI 在汽车领域的可能应用
• GenAI 在汽车供应链中的可能用例
• 汽车供应链中的 GenAI – 应用确定性
• 供应链中的 GenAI – 重点

GenAI 在製造业的应用

• GenAI 在汽车产品设计中的可能用例
• 选择 GenAI 影像生成工具
• 案例研究- 产品设计 - 丰田
• 案例研究——法拉利
• GenAI 在汽车设计上的应用确定性
• GenAI 在汽车生产中的可能用例
• GenAI 在汽车生产上的应用确定性
• OEM在生产现场采用 GenAI
• 案例研究 -梅赛德斯-奔驰
• GenAI 在製造业的概述—要点

GenAI 在汽车零售的应用

• GenAI 在汽车零售领域的可能用例
• 案例研究—行销：雷克萨斯/丰田
• 汽车零售－由 GenAI 提供支援的销售场景
• 案例研究- 销售：Fullpath
• 案例研究- 销售：BMW + 埃森哲
• 案例研究- 客户管理：福特
• GenAI 在汽车零售的应用确定性
• GenAI 在零售业的概述—要点

车载 GenAI

• 车载 GenAI 的可能用例
• OEM推出基于GenAI的语音助手
• 案例研究– 蔚来AI语音助手
• 案例研究 -梅赛德斯-奔驰
• 案例研究—语言在地化：KIA
• 汽车供应商转向 GenAI 语音助手
• 案例研究—Soundhound AI
• 案例研究- 大陆集团和谷歌
• 案例研究- Cerence-Skoda
• 车载 GenAI - 应用确定性
• 车载 GenAI - 要点

超越车辆生命週期

• GenAI 在 AV 中的可能用例
• 不断发展的GenAI在AD中的案例研究
• 案例研究- Forvia Hella
• GenAI 在共享出行领域的可能用例
• 案例研究- Turo
• GenAI 在物流的可能用例
• GenAI 在物流中的用例场景
• GenAI 超越车辆生命週期—重点

成长机会宇宙

• 成长机会1：人工智慧语音助理的订阅收益
• 成长机会二：人工智慧驱动製造时代的到来
• 成长机会3：转变客户参与

附录与后续步骤

• 成长机会的益处和影响
• 后续步骤Next steps
• 文件清单
• 免责声明

Generative AI will Disrupt the Automotive Value Chain in the Next Decade, Most Immediately Inside the Vehicle Cabin through Generative AI Voice Assistants

Generative AI (Gen AI) continues to create an impact across industries including automotive. In the next decade, Gen AI is expected to significantly influence automotive value chains, increase efficiency, productivity, and reduce wastes. In the supply chain, it will be used to optimize inventory and demand forecasting while in product development it can be used to generate design ideas, accelerate prototyping, testing and to shorten the time-to-market. In manufacturing, it can be used to reduce bottlenecks on the assembly line and provide real time insights to production engineers to make informed decisions. In retail, it can be used to provide 24x7 sales support to dealerships executing human- like interactions with potential customers. Inside the vehicle, Gen AI- driven voice assistants will become standard features in the next decade. Beyond the automotive lifecycle, Gen AI will make a significant contribution towards autonomous vehicle development and operation. Gen AI start-ups which focus on solutions for autonomous vehicles will crop up in the coming decade driving innovation and fast tracking the development of such vehicles. Gen AI will support shared mobility by helping increase the efficiency of fleet management, ride booking, pricing, and route planning. In logistics, it will play a key role in choosing the optimal vehicle for a trip, plan routes based on real time traffic data, and customer support functions. Gen AI will also play a key role across various corporate functions including Finance, Human Resources, and Marketing.

Scope of Analysis

• Examine possible generative AI use cases in the automotive value chain.
• Look at evolving use cases and analyze them to understand their impact on the future automotive value chain.
• Break down the automotive value chain into subsegments and discuss potential applications.
• Analyze generative AI's potential integration into existing automotive products and solutions.
• Examine the challenges associated with generative AI in the workplace and use cases that highlight the concerns regarding this technology.
• Derive growth opportunities and key takeaways stemming from the analysis.

Growth Drivers

The Rapid Technological Transformation in the Automotive Industry:

The automotive industry has seen transformational shifts in the past decade, with automakers embracing innovative technologies to digitize operations. GenAI will augment this transformation.

Endeavor to Enhance the In-Cabin Experience:

Automakers are always on the lookout for ways in which they can enhance the in-cabin experience for their customers. GenAI will enable OEMs to offer next-generation human-machine interfaces through GenAI-powered voice assistants.

Improve Efficiency and Profitability:

GenAI can help automate redundant tasks and, coupled with a voice assistant, provide real-time status updates on active tasks, thereby increasing the efficiency of decision-making. This leads to reduced operational tasks and a better bottom line.

Focus on Increasing the Quality of Customer Engagement:

Companies intend to enhance customer engagement and satisfaction by leveraging new technologies. GenAI enables companies to increase the efficiency of customer support chatbots, facilitating 24/7 support in natural languages.

Growth Restraints

Data Privacy Concerns:

Instances of sensitive company data leaking into the public domain through GenAI applications make companies uneasy and apprehensive about adopting this technology.

Issues with Reliability:

GenAI tools have been found to hallucinate and give out factually incorrect information, which could be seen as an unreliable technology in the short term. As the technology matures, the accuracy will improve.

Regulatory Issues:

Governments could view GenAI suspiciously over the ethics around the use of it by companies and common citizens, and the negative impact it can have on various facets of society. This could result in adverse regulations against the use of GenAI.

Practicality:

For organizations to effectively leverage the power of GenAI, they need large datasets and significant computing power. This could be difficult to achieve for organizations in the short term.

Impact of the Top 3 Strategic Imperatives on GenAI in Automotive Market

Customer Value Chain Compression

• Generative AI (GenAI) can automate customer interaction touchpoints that could not be automated efficiently earlier.
• GenAI can understand customer requirements and respond accordingly, almost creating a humanlike conversation when coupled with a voice assistant.

Disruptive Technologies

• GenAI is a disruptive technology that can ease the workload and support employees in an organization to achieve their goals faster and with greater accuracy and efficiency.

Industry Convergence

• GenAI large language models (LLMs) offer numerous possible use cases for all industries, including automotive.
• GenAI has the potential to accelerate innovations in next-generation technologies and products.

Table of Contents

Scope

• Scope of Analysis
• Why is it Increasingly Difficult to Grow?
• The Strategic Imperative 8
• Impact of the Top 3 Strategic Imperatives on GenAI in Automotive Market
• Growth Environment: Transformation of GenAI in Automotive
• Key Takeaways
• Key Automotive Ecosystem Players Using GenAI
• Key Automaker GenAI Use Case By Value Chain
• GenAI Types and Impact on Automotive Use Case by 2030
• Potential Applications of GenAI in Key Corporate Functions
• Car Models with GenAI Voice Assistants
• Price to Access GenAI Voice Assistants in Cars
• GenAI in Automotive-Current Adoption vs Future Impact
• Case Study-Valeo

Growth Generator in GenAI in Automotive

• Growth Drivers
• Growth Restraints

Overview of GenAI

• Key Reasons for Organizations to Adopt GenAI
• GenAI Vs Traditional AI
• The Automotive GenAI Ecosystem-Key Stakeholders
• Select GenAI Tools by Application
• Most Popular GenAI Tools
• IT Decision-Makers' Perception Towards GenAI
• Challenges-Concerns Around GenAI in Organizations
• Emerging AI Regulations by Key Regions
• Overview of GenAI-Key Takeaways

GenAI in Supply Chain

• Snapshot of Possible GenAI Applications in Automotive
• Possible Use Cases of GenAI in Automotive Supply Chain
• GenAI in Automotive Supply Chain-Certainty of Application
• GenAI in Supply Chain-Key Takeaways

GenAI in Manufacturing

• Possible Use Cases of GenAI in Automotive Product Design
• Select GenAI Image Generator Tools
• Case Study-Product Design-Toyota
• Case Study-Ferrari
• GenAI in Automotive Design-Certainty of Application
• Possible Use Cases of GenAI in Automotive Production
• GenAI in Automotive Production-Certainty of Application
• GenAI Adoption by OEMs in Production
• Case Study-Mercedes-Benz
• Overview of GenAI in Manufacturing-Key Takeaways

GenAI in Automotive Retail

• Possible Use Cases of GenAI in Automotive Retail
• Case Study-Marketing: Lexus/Toyota
• Automotive Retail-Sales Scenario Using GenAI
• Case Study-Sales: Fullpath
• Case Study-Sales: BMW + Accenture
• Case Study-Customer Management: Ford
• GenAI in Automotive Retail-Certainty of Application
• Overview of GenAI in Retail-Key Takeaways

In-Vehicle GenAI

• Possible Use Cases of In-Vehicle GenAI
• OEMs with GenAI-Powered Voice Assistants
• Case Study-Nio AI Voice Assistant
• Case Study-Mercedes-Benz
• Case Study-Linguistic Localization: KIA
• Automotive Suppliers Focus on GenAI Voice Assistant
• Case Study-Soundhound AI
• Case Study-Continental & Google
• Case Study-Cerence-Skoda
• GenAI in the Vehicle Cabin-Certainty of Application
• GenAI in the Vehicle Cabin-Key Takeaways

Beyond the Automotive Life Cycle

• Possible Use Cases of GenAI in Autonomous Vehicles
• Evolving GenAI Case Studies in Autonomous Driving
• Case Study-Forvia Hella
• Possible Use Cases of GenAI in Shared Mobility
• Case Study-Turo
• Possible Use Cases of GenAI in Logistics
• GenAI Use Case Scenario in Logistics
• GenAI Beyond Automotive Life Cycle-Key Takeaways

Growth Opportunity Universe

• Growth Opportunity 1: Subscription Revenue Through Generative AI Powered Voice Assistants
• Growth Opportunity 2: Usher in an Era of AI-driven Manufacturing
• Growth Opportunity 3: Transform Customer Engagement

Appendix & Next Steps

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