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.Generative AI will Disrupt the Automotive Value Chain in the Next Decade, Most Immediately Inside the Vehicle Cabin through Generative AI Voice Assistants
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
Growth Generator in GenAI in Automotive
Overview of GenAI
GenAI in Supply Chain
GenAI in Manufacturing
GenAI in Automotive Retail
In-Vehicle GenAI
Beyond the Automotive Life Cycle
Growth Opportunity Universe
Appendix & Next Steps
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Accenture
- BMW
- Cerence-Skoda
- Continental
- Ferrari
- Ford
- Forvia Hella
- Fullpath
- KIA
- Lexus/Toyota
- Mercedes-Benz
- Nio
- Soundhound AI
- Toyota
- Turo
- Valeo