Predictions that artificial intelligence will soon invade every aspect of modern life are a cliché by now, but this world-changing technology has found its way into the automotive world ahead of schedule. From voice recognition to satellite navigation, the most primitive forms of artificial intelligence have been part of the driving experience for more than a decade. These functions are programmed responses to instructions or other human input. Such systems understand commands and execute commands. Advanced AI is thinking about this era and seeks to understand, inform, predict and enhance human performance.
To that end, the artificial intelligence that will be integrated into vehicles of 2026 is evolving faster than it can be implemented, inspiring a variety of opinions about where everything is headed and how the technology can be used. From the automaker’s perspective, McLaren’s production of luxury hypercars and its management of a globally competitive Formula 1 racing team require the inclusion of the latest AI capabilities. According to Christoph Mayer, the automaker’s chief program officer, McLaren’s AI story focuses on the huge efficiencies it can create in the design and engineering phase, which they refer to as “AI-enhanced engineering.” “In terms of our use of AI in engineering and design, McLaren Automotive is transforming its future product development by incorporating truly end-to-end AI across the entire engineering lifecycle,” he told the Observer.
For starters, agent AI can follow detailed instructions without supervision, set its own goals, create detailed plans and carry out any relevant tasks using its chosen external tools or systems. “McLaren applies a ‘just right’ AI package to deliver speed and scale throughout the engineering design and development process,” added Mayer. “The team can now explore more of the design space, perform complex tests and simulations at an incredible pace, fine-tune each component with greater precision and reduce manual and repetitive tasks by leveraging geometric factors.”
Mayer insists that the resulting environment allows teams to focus on high-value design and engineering thinking, while leaving process-level tasks to AI.
Sam Abu Al-Samid is Vice President of Market Research at Telemetry, a transportation and mobility research and consulting practice. With a focus on assisted and automated driving and mobility services, he believes the most profound impact of AI in the near future will be the continued removal of humans from the driving process: “The biggest consumer-facing application of AI is advanced driver assistance systems – especially the latest hands-free systems like Super Cruise (from General Motors). It’s still relatively new for most automakers, but Tesla has shifted its entire suite of driver assistance systems to rely on AI models. Mercedes-Benz uses Nvidia’s Alpamayo and both companies rely on Lucid And Jaguar Land Rover has this system as well, as Nissan and Stellantis also announced plans to introduce the next generation of advanced driver assistance systems based on the Wayve artificial intelligence system in the next two years.
Abu Al-Samid expects the market to see increased use of AI in areas such as powertrain and chassis control. “The AI model can manage aspects such as engine control and battery charging and discharging to improve efficiency for better range. For this to work, the AI models need to run in real-time on the vehicle rather than in the cloud.”
According to Dr. Liucheng Guo, CTO and co-founder of TGO, a London-based company working on sensor technology for car interiors, current AI is increasingly about understanding the real-time state of the driver, passengers and car environment. “This includes driver assistance, occupant monitoring, safety intervention, predictive maintenance, and more adaptive human-machine interfaces,” Guo told the Observer. “We see a huge opportunity in pressure mapping and integrated materials sensing. A seat, armrest, steering wheel or interior surface could become a smart sensing layer.”
For example, Joe explained, a camera can be used during development to train an AI model to understand body posture, position, and user intent, but the production vehicle doesn’t need to rely on the camera. “The system can infer the occupant’s position and condition from pressure and touch data alone. This creates a more privacy-preserving, non-intrusive way for the car to understand what’s happening inside the cabin.”
Gu rejected the idea that AI thinks like a human brain, but stressed that it could react much faster in safety-related situations, process more data or take on tasks that people cannot do consistently or do not want to do frequently. “Useful AI in a car doesn’t necessarily mean trying to imitate someone,” he said. “Its value lies in identifying signals that humans might miss, such as a change in position, a child seat not secured, a passenger out of position, a driver shifting weight before gaining control or a person becoming unstable or uncomfortable.”
Gu does not see the human being replaced by a car that thinks for him or her, but rather calmly and naturally supports the user: “The passenger must simply sit and move naturally, and the car must understand enough to adapt. This is especially important for senior-friendly and accessibility-focused design where the best interface may not be a visual one at all in custom, safety-conscious, customized cabins.”
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