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Automotive 2024: Industry Leaders Chart Course to AI-Driven Supply Chains by 2034

Industry giants like Ford and Honda shared their digital transformation journeys. The future? Generative AI and large language models promise to revolutionise supply chains by 2034.

This picture contains a box which is in red, orange and blue color. On the top of the box, we see a...
This picture contains a box which is in red, orange and blue color. On the top of the box, we see a robot and text written as "AUTOBOT TRACKS". In the background, it is black in color and it is blurred.

Automotive 2024: Industry Leaders Chart Course to AI-Driven Supply Chains by 2034

The Automotive Logistics & Supply Chain Digital Strategies North America 2024 conference wrapped up with a focus on the future of digitalisation. Key industry figures shared insights on global data demand, digital transformation, and the potential of AI in supply chain management.

Ford's Ed Stachowski kicked off the discussions, highlighting the growing demand for global data and analytics across various business units such as logistics, production, and purchasing. Meanwhile, Honda's Logen Lytle delved into the carmaker's digital transformation journey, revealing the setup of specialist units for technology application.

The final day also explored the foundational pillars for the next step in digitalisation. Ford's Becca Adam stressed the importance of understanding the problem at hand and aligning goals across business divisions for successful digitalisation. Looking ahead to 2034, Gerardo de la Torre and Rajeev Puri discussed the potential of generative AI and large language models in transforming supply chains. Experts also explored increasing automation through data analytics and scaling AI use across logistics and supply chain networks.

The conference concluded with a clear vision for the future of automotive supply chains. Industry leaders agreed on the importance of data, digital transformation, and AI for driving efficiency and innovation. As the industry looks towards 2034, the potential of generative AI and large language models emerged as a key topic for further exploration.

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