Early Generative AI and its impact on Automotive industry, 2023 summary

Impact on Operations and Industry Transformation

Top consulting companies say Generative AI (GenAI) will change the automotive industry in many ways. They report that AI improves production, reduces equipment costs, and develops autonomous vehicles. AI also affects research, design, project management, and business support functions. Investments in AI and IoT devices improve how vehicles are made and used.

The leading consultancies rank AI, including GenAI, as the best technology for disrupting manufacturing. Their survey shows that executives expect AI to boost productivity, helps create the factory of the future, with assistance, recommendation, and autonomous systems for the automotive industry. 

Top consultancies agree that AI will change not only vehicles but also how automotive companies work. They suggest that automotive companies should use AI and build an AI-ready culture. Most leaders in the automotive sector confirm that their companies are experimenting with the GenAI. They also say, however, that it is not straightforward to gain significant business case from the current showcases.

Areas of Greatest Impact

The areas of greatest impact of Generative AI on the automotive industry are outlined in the document. Top consulting companies agree that Generative AI will change the automotive industry in many ways, including improving production, reducing equipment costs, and developing autonomous vehicles. AI also affects research, design, project management, and business support functions. Investments in AI and IoT devices improve how vehicles are made and used. These all contribute to the larger business case. It is clear, that there is no one standalone tool that leads to immediate significant gain.
Deloitte is continuously making the effort the to update the library of tangible use cases, the Generative AI Dossier. The top use cases the top consultancies mostly align on:

The crux is that the automotive industry is on the cusp of a major shift driven by AI innovations and newcomers to the industry. This shift will likely influence every stage of the automotive value chain, from production to post-sale services. The implementation pace and integration of AI technologies by automotive companies will essentially dictate market competitiveness and long-term success. The distinctions become less important as they collectively underscore the urgency with which the automotive sector must approach the adoption of AI technologies.

Security and Compliance Challenges

Deploying generative AI brings governance and risk mitigation to the forefront as business imperatives. Traditional AI challenges are amplified with generative AI, making a commitment to trustworthy development and use of these technologies more important as capabilities grow and as regulatory bodies shape rules for their application.The companies should pay specific attention to the following points:

1. Governance and risk mitigation as imperative tasks, particularly as AI capabilities expand and regulation evolves.
2. The rapid evolution of technology creating challenges in maintaining up-to-date practices in legal and compliance issues.
3. Intellectual property and data privacy concerns around the legality of training data and the protection of proprietary information.
4. Trust domains that need to be managed with care to ensure AI systems are fair, reliable, transparent, and respectful of privacy.
5. The risk of generative AI "hallucinations" where AI models produce outputs that seem accurate but are not based on reality, impacting user trust.
6. Challenges related to bias and misinformation that could arise from AI systems that reflect training set biases.
7. A need for transparency and accountability, especially as outputs become more complex and difficult to interpret or validate
8. Single cloud strategy makes the companies can lead to new vendor lock – mainly in the data space.
9. Potential for economic disparity as the use of generative AI could concentrate power and magnify inequality.
10. Regulatory uncertainty due to the pace of AI development potentially outpacing existing legal frameworks.
11. Managing talent and ensuring organizational readiness to address technological, governance, and risk concerns of generative AI deployment.

Conclusion

As per the Deloitte Automotive 2024 study, the automotive industry is set to experience dynamic shifts with the entrance of consumer electronics brands. These new players bring expertise in connectivity and infotainment systems—areas of high interest to consumers—challenging traditional automakers to innovate similarly. Price sensitivity and the desire for greener models are significant drivers for consumers considering brand switches, underscoring the need for established companies to adapt to changing preferences. Brand loyalty varies with more pronounced loyalty in developed markets, prompting traditional manufacturers to leverage their reputations while also focusing on affordability and sustainability to stay competitive. Trust in managing connected data remains predominantly with car manufacturers, but skepticism from some consumers presents monetization challenges for both new entrants and veteran companies.

Generative AI is set to affect all departments within automotive companies and it’s important to start adopting the technology promptly to harness its benefits while effectively managing its challenges. Leaders involved in piloting or implementing generative AI are optimistic but also recognize significant challenges. A vast majority, 79%, expect generative AI to drive substantial transformation within their organizations and industries over the next three years. Leaders acknowledge that the trajectory of their current decisions could significantly affect future outcomes as they balance the prospect of speed and value against managing potential risks and societal impacts.

Interestingly, leaders who self-assess their organization's expertise in generative AI as very high also tend to report higher levels of trust and lower levels of uncertainty. These leaders also view widespread adoption as both an opportunity and a threat, placing them under greater pressure to adopt and scale generative AI initiatives.

In conclusion, while leaders, consultancies, and independent researchers are cognizant of the transformative power of generative AI, the early adopters are already actively making efforts to recruit technical talent, educate their workforce, and reskill workers affected by generative AI. There's a general acknowledgment that more substantial measures are needed to fully leverage the capabilities of generative AI.

Sources:

https://www2.deloitte.com/us/en/pages/consulting/articles/state-of-generative-ai-in-enterprise.html

https://www2.deloitte.com/us/en/pages/consulting/articles/generative-ai-for-enterprises.html

https://www2.deloitte.com/us/en/pages/consulting/articles/trusted-generative-ai.html

https://www.deloitte.com/global/en/services/legal/services/generative-ai-legal-departments.html

https://www.bcg.com/publications/2023/gen-ai-role-in-factory-of-future

https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year

https://www2.deloitte.com/us/en/pages/consumer-business/articles/global-automotive-consumer-study.html

https://www2.deloitte.com/us/en/pages/consulting/articles/gen-ai-use-cases.html