The automotive industry is being shaped by key trends which include the rapid adoption of electric vehicles, the shift toward software-defined vehicles, and the integration of connected and autonomous features.
With emergence of Generative AI, there is potential to revolutionize design, engineering, R&D in these areas. The key advantages, that Generative-AI for Automotive brings are reduced cost, faster time to market and innovative solutions. Additionally with integration of Gen-AI, there is potential to revolutionize driver experience, improve sustainability and many more.
Shift from AI to Gen-AI
Gen-AI comes with ability to generate novel content beyond their training data. Though Gen-AI buzz has been recent, it’s based on deep neural networks that has been incrementally developed since 1950s. Traditional AI excels in analytics and solving specific objectives, while Gen-AI adds a new paradigm of being creative and dynamic. It comes with capability to generate new content such as text, code, image, audio, video as well as being conversational. With these capabilities, it can be applied to wide range of applications across industries.
Gen-AI Impact on Automotive Industry
Key areas that would be impacted by Gen-AI for Automotive Industry
Generative-AI for Automotive would be highly impacted by the key areas of R&D, Engineering, Product development and creative solution development. In Design and Engineering space, Gen-AI would enable Quality and Delivery excellence through Auto code generation, Auto test data and Test case generation, Compliance verification ensuring end-to-end traceability.
Another potential use case could be personalized in-vehicle experience, personalized trip recommendations and interactive in-car driver assistance. Gen-AI’s natural language capabilities will enable highly engaging and meaningful in-vehicle experiences.
Additionally, Gen-AI will bring enormous benefits for Autonomous Driving / ADAS development with synthetic data generation, object detection and tracking, simulated diverse scenario generation and scene understanding.
Sales, Marketing, Supply chain management is one more area where in Gen-AI can offer pricing optimization, inventory optimization with demand forecast.
Risks and Considerations
Although Generative AI has the potential to revolutionize the industries and societies, it carries risks. The key risks that need to be addressed by organization and policy makers are:
- Security, Data Privacy, Intelligent Property Protection
- Transparency
- Bias, Hallucinations,
- Over-reliance on AI
- Ethical AI use
To address these risks, measures that needs to be taken includes establishing strong governance practices, establishing data protection framework, building strong risk management framework and empowering responsible AI Use.
Framework for Implementation
For adoption of Gen-AI, we recommend strong governance and implementation framework with below considerations:
Framework for Gen-AI Implementation
Identify Potential Use Case: Evaluate and identify impactful use case
Assess Data Readiness: Establish Data Management and Engineering framework. Establish data pipeline. Ensure high quality, diverse data
Implement Pilot: Develop minimum viable model Review, Feedback and Adopt: Ensure iterative development approach with continuous performance monitoring, review and feedback incorporation.
Governance Framework: Develop framework for responsible AI use, addressing biases and emphasising on transparency
Data Protection, and Privacy Guidelines: Ensure robust IP policy, and Privacy checks
Risk Management: Ensure strong Risk Management plan. Conduct accuracy and reliability tests.
Scale: Enhance and scale
The way ahead
While Gen-AI technology is still evolving, potential benefits and use cases for the Automotive industry are numerous, offering opportunity to gain a competitive advantage, making it worth pursuing.
Effective adoption of Gen-AI for Automotive use cases requires skilled AI experts, deep domain understanding and robust governance framework. At Tata Elxsi, leveraging our domain expertise in Automotive, and with robust AI skills, we have effectively executed pilots/solutions ranging from Design and Engineering to Feature/ Solution development. Furthermore, we create a robust governance framework for its implementation.
Date: July 2024
