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Karl Clark spent 30 years in the automotive industry at Ford before taking a voluntary separation package and founding B.I.G. Intelligence AI, a technical engineering, consulting and services company. In this conversation with Sunny Ray, Clark explains how cars became computers on wheels, why over the air updates matter to capital intensive automakers, and what he saw inside large companies that pushed him to leave. He describes how heavy daily AI use has raised his own productivity at least fivefold, and why that gain has not yet reached large enterprises. Clark outlines why engineering teams resist new tools, how entrenched product development processes and supplier software suites make adoption difficult, and why compliance requirements such as ISO 27001 slow onboarding. His company focuses on the design and requirements phase, including model based systems engineering and failure mode analysis. He also discusses investors with automotive connections, a chess-trained analytical mindset, and a bold prediction that designing a car could take 90 days within ten years.
After 30 years at Ford, Karl Clark bet on AI to automate car design, and says his own productivity is already up fivefold.
What is B.I.G. Intelligence and what problem does it solve?
B.I.G. Intelligence AI is a technical engineering, consulting and services company. One major track is automating the automotive product development process, particularly for software defined vehicles. We also help companies integrate AI automations and improve their workflow and process efficiency.
What did you see inside the industry that made you leave Ford?
I saw a shift in how companies manage people, including pushing people out through performance reviews and cutting the lowest 10%. I didn't like that part of the job. When I was offered a voluntary separation package, I took it as my chance to leave that stress behind and do my own thing.
Why do over the air updates matter to automakers?
Software keeps changing, so you need a way to get it into vehicles you sold yesterday. Automotive is capital intensive compared to software companies. Automakers want to monetize through continuous touch points with customers, selling new products and services across the full life cycle of the vehicle.
How has AI changed your own productivity?
I work 70 to 80 hours a week with AI, and I'd say my productivity has increased at least five times, which I think is conservative. I've done engineering for 30 years, so I know the job, and the capability still blows my mind. Companies aren't seeing these gains yet, but it's coming.
Why do engineering teams resist new tools, and how do you win them over?
Large automakers have institutionalized product development processes, so dropping in a new tool is nearly impossible. It usually has to start with an advanced team that tests and learns to trust it, then win over leadership. Supplier suites from companies like Siemens and Bosch make integration harder, but the efficiency gains are too big to ignore.
Where in product development does your technology focus?
We focus on the design and requirements side: what the product must do and how to make it robust, considering failure modes and mitigations. AI can auto-generate code quickly, but the question is whether that code is any good. Good requirements and designs are where I see many problems in the field.
Why do you want investors who know automotive?
In the age of AI you don't need as much money to build a software product. What matters more is connections. Investors with deep automotive ties can call OEMs and tier ones, get advanced teams to evaluate the product, and reach chief engineers and directors who make the decisions.
Ten years from now, how long will it take to design a new car?
I'd say 90 days, down from around 15 months today. Anyone can design a car in theory, but designing one I would want to ride in is different. You still need someone who understands what's going on, because I'm not going to risk my life in something unproven.
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