生成式人工智慧 (GenAI) 及其在汽車領域的應用案例的策略性洞察

生成式人工智慧將在未來十年顛覆汽車價值鏈

生成式人工智慧 (GenAI) 持續影響著包括汽車在內的各行各業。未來十年，GenAI 預計將對汽車價值鏈產生重大影響，提高效率和生產力，減少廢棄物。在供應鏈中，它將有助於最佳化庫存和需求預測；在產品開發中，它將有助於產生設計理念，加速原型設計和測試，並縮短產品上市時間；在製造中，它將有助於消除組裝上的瓶頸，並為生產工程師提供即時洞察，以便他們做出明智的決策；在零售中，它將為經銷商提供與潛在客戶的十年，並實現與潛在客戶的類人互動；驅動的車載語音助理將成為一項標準功能；在汽車生命週期之外，GenAI 還將為自動駕駛汽車的開發和營運做出重大貢獻；未來十年，將湧現出一批專注於自動駕駛汽車解決方案的 GenAIStart-Ups，推動創新並加速自動駕駛汽車的發展。 GenAI 將透過協助簡化車隊管理、乘車預訂、定價和路線規劃來支援共享出行。在物流領域，它在選擇最佳車輛、根據即時交通數據規劃路線、客戶支援功能以及企業的其他各種功能（包括財務、人力資源和行銷）中發揮著至關重要的作用。

目錄

分析範圍

GenAI 在汽車領域的成長引擎

• 成長動力
• 成長抑制因素

GenAI概述

• 組織採用 GenAI 的主要原因
• GenAI 與傳統 AI
• GenAI 汽車生態系統－關鍵相關利益者
• 按應用程式選擇 GenAI 工具
• 最受歡迎的 GenAI 工具
• IT 決策者對 GenAI 的看法
• 挑戰－組織對 GenAI 的擔憂
• 主要地區新興人工智慧法規
• GenAI 概述 – 要點

供應鏈中的 GenAI

• GenAI 在汽車領域的可能應用
• GenAI 在汽車供應鏈中的可能用例
• 汽車供應鏈中的 GenAI – 應用確定性
• 供應鏈中的 GenAI – 重點

GenAI 在製造業的應用

• GenAI 在汽車產品設計中的可能用例
• 選擇 GenAI 影像生成工具
• 案例研究- 產品設計 - 豐田
• 案例研究——法拉利
• GenAI 在汽車設計上的應用確定性
• GenAI 在汽車生產中的可能用例
• GenAI 在汽車生產上的應用確定性
• OEM在生產現場採用 GenAI
• 案例研究 -梅賽德斯-奔馳
• GenAI 在製造業的概述—要點

GenAI 在汽車零售的應用

• GenAI 在汽車零售領域的可能用例
• 案例研究—行銷：雷克薩斯/豐田
• 汽車零售－由 GenAI 提供支援的銷售場景
• 案例研究- 銷售：Fullpath
• 案例研究- 銷售：BMW + 埃森哲
• 案例研究- 客戶管理：福特
• GenAI 在汽車零售的應用確定性
• GenAI 在零售業的概述—要點

車載 GenAI

• 車載 GenAI 的可能用例
• OEM推出基於GenAI的語音助手
• 案例研究– 蔚來AI語音助手
• 案例研究 -梅賽德斯-奔馳
• 案例研究—語言在地化：KIA
• 汽車供應商轉向 GenAI 語音助手
• 案例研究—Soundhound AI
• 案例研究- 大陸集團和谷歌
• 案例研究- Cerence-Skoda
• 車載 GenAI - 應用確定性
• 車載 GenAI - 要點

超越車輛生命週期

• GenAI 在 AV 中的可能用例
• 不斷發展的GenAI在AD中的案例研究
• 案例研究- Forvia Hella
• GenAI 在共享出行領域的可能用例
• 案例研究- Turo
• GenAI 在物流的可能用例
• GenAI 在物流中的用例場景
• GenAI 超越車輛生命週期—重點

成長機會宇宙

• 成長機會1：人工智慧語音助理的訂閱收益
• 成長機會二：人工智慧驅動製造時代的到來
• 成長機會3：轉變客戶參與

附錄與後續步驟

• 成長機會的益處和影響
• 後續步驟Next steps
• 文件清單
• 免責聲明

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