Ford’s AI chief Bryan Goodman reveals how AI models like OpenAI, Anthropic, and DeepSeek are transforming vehicle design to compete with fast-moving rivals.
Ford Motor Company is ramping up its use of artificial intelligence (AI) to streamline vehicle design and engineering, as it seeks to match the speed of global competitors, particularly Chinese automakers. Bryan Goodman, Ford’s Director of Artificial Intelligence, emphasized the need for faster development cycles to remain competitive in the evolving automotive landscape.
Ford has faced challenges in recent months, including sluggish demand for electric vehicles, increasing competition, and new U.S. tariffs. While the company reported higher revenue for the fourth quarter of 2024, its outlook for 2025 disappointed investors, leading to a decline in its stock value. Against this backdrop, Ford is turning to AI to optimize its engineering and production processes.
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AI’s Role in Accelerating Design and Testing
Currently, Ford’s vehicle design process involves sculpting new models out of clay before engineers conduct extensive simulations and stress tests. This method, while effective, is time-consuming. AI is now being integrated to automate portions of this process, reducing development time. Goodman highlighted AI’s ability to convert designers’ 2D sketches into 3D models and renderings, seamlessly connecting design with engineering.
Ford is also utilizing AI to conduct predictive stress tests and other physics-based assessments, such as computational fluid dynamics and wind tunnel drag simulations. Traditionally, these tests could take up to 15 hours, but AI models now enable results in just 10 seconds, significantly enhancing efficiency.
AI Models and Infrastructure
To power its AI-driven initiatives, Ford is leveraging a mix of AI models, including those from OpenAI, Anthropic, and DeepSeek. Goodman noted that while DeepSeek has proven to be a strong model, it does not necessarily outperform offerings from Anthropic, Google’s Gemini, or OpenAI. However, DeepSeek’s open-source nature provides added flexibility for Ford’s AI applications.
Ford primarily runs its AI workloads on its own Nvidia GPUs, with thousands deployed across its infrastructure. The company moved most of its operations to the cloud years ago, but high-performance GPU computing remains on-premises due to cost and availability constraints. Goodman compared securing cloud-based GPU resources to obtaining Taylor Swift concert tickets—both are in high demand and come with a hefty price tag.
Challenges with Next-Gen AI Hardware
Ford is preparing for the arrival of Nvidia’s next-generation Blackwell chips, which promise significant advancements in AI computing power. However, the company has yet to receive the new hardware. Nvidia CEO Jensen Huang has positioned Blackwell as a game-changer, suggesting that it will render its predecessor, Hopper, obsolete. Goodman, however, believes Hopper GPUs will continue to be valuable for the next few years.
One of the key challenges Ford faces in integrating Blackwell chips is their increased power consumption. Goodman revealed that major electrical upgrades are necessary to accommodate the new hardware, with even more extensive modifications anticipated for future Nvidia chip generations like Rubin and Feynman.
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The Evolution of AI in Automotive and Tech Conferences
Goodman, a regular attendee of Nvidia’s annual GPU Technology Conference (GTC) in San Jose, California, has witnessed firsthand the rapid evolution of AI applications in the automotive sector. He noted that GTC has grown significantly over the past decade, drawing larger crowds and making it more difficult to engage with industry leaders like Nvidia’s Jensen Huang.
As Ford continues to integrate AI into its design and engineering processes, the company is positioning itself to compete more effectively in a rapidly changing automotive industry. By harnessing AI’s capabilities, Ford aims to enhance efficiency, reduce development timelines, and stay ahead in an increasingly AI-driven market.
