Beyond the Buzz: AI in the automotive industry

AI in the automotive industry is a powerhouse, reshaping everything from safety features to assembly lines. But with this power comes a truckload of headaches — data privacy concerns, algorithm bias and the looming question of who’s really in the driver’s seat when it comes to decision-making.

To navigate this complex landscape, S&P Global Mobility turned to the insights of AI specialists to uncover the potential and pitfalls of this transformative technology.

Driving simulations

AI excels in creating advanced simulations that not only meet, but exceed, safety regulations, fostering consumer trust in our increasingly connected vehicles. “The automotive industry is on the cusp of a transformative shift driven by AI,” said Moritz Neukirchner, senior director of strategic product management at Elektrobit. “Generative AI is a key player, delivering personalized experiences and streamlining development. We also see huge potential in reinforcement learning for [enhancing] ADAS and autonomous driving.”

“Vehicles, which today are controlled by distributed electronic control units, are increasingly moving to centralised high-performance computing,” said Mazen El Hout, senior product marketing manager at Ansys. “This architecture is the key to integrating the growing number of software functions — from ADAS to over-the-air updates — efficiently and securely. How do we manage this complexity? I expect simulation and test platforms to play a crucial role, especially in verifying software updates for older vehicle models.”

AI is reshaping manufacturing by optimizing processes from design to production. For example, Ford is using AI to enhance assembly lines, reduce waste and boost productivity. AI also improves human-robot collaboration, allowing robots to handle repetitive tasks, increasing safety and efficiency in the workplace.

Driven by data

“We're seeing GenAI adaptations dive deeper into the value stream of carmakers, with models tailored for specific processes,” said Matthias Bauhammer, director of data & AI, automotive & manufacturing at DXC Technology. “One of the biggest potentials we see is in the test and validation process.”

AI improves predictive maintenance, allowing manufacturers to spot potential problems before they escalate. General Motors uses AI to sift through real-time data from connected vehicles, sending alerts to drivers. This proactive approach slashes downtime, cuts maintenance costs and extends vehicle lifespans.

As vehicle autonomy progresses, edge computing is stepping into the spotlight. This tech enables lightning-fast AI processing in vehicles, ditching cloud dependency and ensuring critical functions run smoothly, even in tough conditions.

In the supply chain arena, AI can predict demand and optimize inventories. It guarantees that essential parts are on hand while minimizing excess stock, enabling real-time production tweaks and pinpointing the most efficient shipping routes. This boosts operational efficiency and keeps customers happy, even as challenges such as data standardization and algorithm bias lurk.

The race to elevate customer experiences is intensifying and many automakers are going all in on AI. They are launching personalized services and savvy virtual assistants that turn mundane interactions into seamless, intuitive journeys. BMW, for instance, is using AI to leverage voice recognition technology, letting drivers command navigation and music with just a word.

“AI is rapidly transforming the user experience in the automotive industry, enhancing both the driving experience and life on board,” said Patrick Nebout, chief technology officer of Yanfeng Technology. “With AI technologies, automotive interiors are becoming smarter, more personalized, and safer, ultimately offering drivers and passengers an intuitive and highly connected experience.”