Unlocking the Power of Data and AI in the Automotive Industry

Today, AI is accelerating every stage of automotive innovation from design to production. In R&D, AI algorithms analyze simulation and testing data to optimize performance, efficiency and sustainability. For example, AI-driven generative design can reduce component weight by up to 20%, improving efficiency without compromising safety. On the shop floor, AI-powered vision systems detect defects in real time, enhancing quality and reducing waste. Combined with virtual twins on the 3DEXPERIENCE platform, engineers can test, validate and refine designs digitally before physical production, cutting time-to-market and cost while reducing prototyping needs.

A software-defined vehicle (SDV) is designed so that its key functions like infotainment, driver assistance, battery management and vehicle dynamics are controlled by software rather than fixed hardware. This allows automakers to deliver new features, performance upgrades and safety improvements through over-the-air (OTA) updates, much like smartphones.

Data is at the heart of this transformation. Connected cars can generate around 25 GB of data per hour, and autonomous vehicles more than 300 TB per year. Harnessing this data enables continuous optimization, predictive maintenance and the creation of personalized in-vehicle services turning cars into intelligent, evolving platforms that improve over time.

Generative AI is becoming a catalyst that drives innovation in automotive design and engineering. It can rapidly create and evaluate thousands of design alternatives, optimizing structures for lightweighting, aerodynamics and energy efficiency while maintaining safety and performance standards. In R&D, generative AI assists engineers by automating repetitive modeling tasks and suggesting new concepts drawn from simulation data, shortening development cycles.

According to McKinsey, applying generative AI in product development could improve R&D productivity by up to10 to 20%. This means faster time-to-market, reduced prototyping costs and more intelligent designs across teams. As the industry moves toward software-defined and data-centric vehicles, generative AI helps engineers focus on what matters most, delivering smarter, safer and more sustainable mobility experiences.

As vehicles become connected and software-driven, they generate vast amounts of data. For example, driving behavior and sensor readings, and maintenance alerts. The challenge for OEMs is no longer collecting data, but turning it into value.

According to PwC, by 2030 nearly 95% of new vehicles sold will be connected, creating unprecedented opportunities for data monetization. This includes new business models such as personalized insurance and in-vehicle entertainment features to subscription-based features and fleet optimization.

To capitalize on this, automakers need unified data architectures that connect information across design, manufacturing and aftersales. The 3DEXPERIENCE platform enables companies to integrate and contextualize this vehicle data in a virtual twin environment. Thereby, allowing teams to simulate, test and optimize performance and customer experience. When properly leveraged, data becomes a strategic asset that fuels innovation and supports the shift toward sustainable, customer-centric mobility.

The rise of data-driven design, automation and generative AI are redefining the skills required across the automotive value chain. Engineers now need to combine traditional mechanical and electrical expertise with software development, data science and systems engineering skills. According to the European Commission, the industry could face a shortage of up to 2.4 million skilled workers by 2030, particularly in software, electronics and digital engineering roles.

To address this, OEMs are investing in upskilling programs, partnerships with universities and tech firms as well as AI training that prepare engineers for the next wave of vehicle development. Some are creating dedicated software hubs or digital academies to strengthen expertise in artificial intelligence, cybersecurity and virtual simulation to ensure their workforce can adapt to the software-defined, AI-driven future of mobility.