KEYNOTE PANEL DISCUSSION

The entire automotive industry is under severe pressure to reduce cost and increase efficiency. By using Generative AI, a leading carmaker has been able to bring down material cost by 18% and weight of certain vehicle components by 23%.

• Join a panel of experts as they discuss new opportunities that Generative AI presents for automotive companies to optimize product process efficiencies, reduce costs, automate tasks, and gain revenue from previously hidden insights and opportunities.

Christopher Simpson

Director, Data Strategy and Analytics
Lear Corporation

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PRODUCT DEVELOPMENT PANEL DISCUSSION

The automotive industry typically spends upwards of $1 billion over several years on new product development, with no guarantee that the gamble will pay off.

One of the world’s biggest vehicle manufacturing companies found a way to convert eighteen components into just five components through a new way of manufacturing using generative AI. With never-before-seen abilities in data synthesis pattern detection and outcome prediction, generative AI models have the potential to reduce the time required for platform/architecture development and vehicle manufacture by three to six months at a minimum.

• Join this panel discussion as attendees learn how to speed up product development, gain efficiencies in product development and reduce the time it takes to get things done.

Jake Tanana

Director of Software, Hardware & Mechanical Engineering
Polaris

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AUTONOMOUS VEHICLE DEVELOPMENT USE CASE PRESENTATION

Generative AI tools have the potential to speed up AV development, supporting three critical layers of R&D. In this session, attendees will learn about the ways in which Generative AI can support autonomous vehicles and autonomous driving by looking at:

• How to create virtual environments and simulate real-world scenarios allowing AVs to learn and adapt in a safe and controlled environment.
• Generating high volumes of synthetic data that represent real-world driving scenarios, thus eliminating the need for expensive and time-consuming field tests.
• Creating sophisticated and practical algorithms that can be used to train decision-making models.

Sneha Shetiya

Staff Software Engineer
Torc Robotics

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USE CASE PRESENTATION & SUBSEQUENT DISCUSSION

In this session, attendees will delve into a case study on how Generative AI can be used as a personalization technique to help improve customer experience and generate something that is specific to the user based on their inputs. Attendees will gain valuable insights into:

• How Generative AI and large language models can provide a unique interface to between the user and the vehicle.
• How to personalize and generate something specific for the user that is unique based on the individual’s inputs.
• How Generative AI enables the vehicle to become an entity that understands exactly what the user is needing it to do, resulting in higher customer satisfaction and value.

Nevi Kaja

Director of AI Engineering
Ford Motor Company

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LEARN HOW TO APPLY GENERATIVE AI TECHNOLOGY WHILE MANAGING DATA PRIVACY RISKS

The more data you have, the better the result is on the Generative AI products. If you don’t have enough data, then you must come up with a workaround; either by trying to embed and anonymize data as much as possible so that it’s untraceable, or you must create data from dust. Both these options are challenging and require a lot of effort from companies themselves. In an ideal world, automotive organizations want the user to agree to sharing data, while preserving privacy and data sovereignty.

Attendees will walk away with a thorough understanding on:

• Regulations around data privacy.
• Measures to manage the social factor of overcoming the user’s fear of sharing private information.
• Smart practices to ensure ethical data usage.
• Preserving data privacy during training on public and private data for LLMs.

In today’s business landscape, Artificial Intelligence (AI) is a critical tool for driving innovation and growth. However, many companies make the mistake of treating AI as a standalone strategy rather than an enabler of broader strategic objectives. This approach can lead to missed opportunities and wasted resources.

In this talk, explore the concept of integrating AI into strategic planning, emphasizing its role as a powerful enabler that can enhance corporate, business, and functional strategies. By aligning AI initiatives with broader business goals, companies can drive sustainable growth and competitive advantage. Discuss practical strategies for integrating AI into existing strategic frameworks, avoiding the pitfalls of ‘AI washing’ and ensuring that AI investments deliver meaningful outcomes. Join us to learn how to leverage AI as a strategic enabler and move beyond the limitations of a standalone AI strategy.

• Discover how to transform your business strategy with AI.
• Avoid the pitfalls of ‘AI washing’ and superficial implementations.
• Learn from real-world case studies and best practices.

Hanan Al Haddi

Guest Lecturer on Strategy | Industry Expert on Strategy and Innovation
University of Oxford | Leading OEM/T1 Supplier

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CLOSING PANEL DISCUSSION

By this point in the day, you will have heard ground-breaking presentations and seen cutting-edge technology demos from some of the pioneering companies and individuals in automotive today. And while the industry is cognizant of the transformative power of Generative AI, there is the recognition that several hurdles will need to be overcome to fully leverage the capabilities of Generative AI.

This panel of experts will wrap up the conference proceedings with a discussion on what needs to be done to manage:

• Pushback from management/staff.
• High investment costs.
• Lack of technical staff, reskilling workers and education.
• Complex regulatory framework.
• Data privacy and IP concerns

Sneha Shetiya

Staff Software Engineer
Torc Robotics

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Hanan Al Haddi

Guest Lecturer on Strategy | Industry Expert on Strategy and Innovation
University of Oxford | Leading OEM/T1 Supplier

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Partha Goswami

Advisory Board Member
formerly Senior Director at General Motors

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