Digital Twins in the Automotive Industry Explained

The automotive sector is deep into its Industry 4.0 transformation, and digital twins are proving central to that shift. In 2024, S&P Global Mobility spoke with leaders from IBM, Ansys, ABB Robotics, rFpro, PTC, and NVIDIA. Their consensus was clear: digital twin adoption is accelerating as vehicle digitization and AI integration become standard.

A digital twin in this context is a virtual model that’s constantly updated with real-world data. In 2025, manufacturers are using them to test designs before building, predict performance issues before they occur, and integrate complex systems like EV batteries and autonomous driving software. Across industries, the global market for digital twins is expanding fast, from USD 21 billion in 2024 to a projected USD 29 billion in 2025, reports the Business Research Company. Automotive is one of the strongest growth areas.

The impact is visible at every stage of the vehicle lifecycle. 

1. Virtual prototypes speed up vehicle design

In the design phase, Ford creates virtual prototypes to refine aerodynamics and structural integrity long before building a physical model. BMW applies digital twins inside its manufacturing plants, improving workflows and reducing downtime. Mercedes-Benz uses NVIDIA Omniverse to optimize assembly layouts and operations.

General Motors uses digital twins for predictive maintenance, allowing them to monitor vehicle performance and anticipate issues before they escalate. Volkswagen optimizes its manufacturing processes by simulating production lines digitally, identifying bottlenecks in real-time. Meanwhile, Audi enhances customer experience through personalization, tailoring vehicle settings based on individual preferences and driving habits.

2. Digital twin technology simulating real-world conditions to boost safety

When it comes to safety, digital twin technology has redefined testing. Waymo’s Simulation City platform mirrors real-world traffic, weather, and road user behavior using more than 20 million miles of driving data. Engineers can run millions of scenarios, even in cities Waymo hasn’t physically mapped, cutting risk, accelerating validation, and reducing the need for costly physical testing.

With Waymo now set to expand across the Bay Area, including San Jose and SFO, the automotive industry is witnessing the powerful impact of digital twin technology to help manage complex infrastructure. Valeo and Applied Intuition are also developing platforms to stress-test advanced driver assistance systems in extreme conditions, all within highly detailed virtual environments.

Similarly, Tesla uses digital twins to simulate crash scenarios, improving vehicle safety designs without extensive physical testing. Volvo also uses digital twins to analyze real-time data from its vehicles, enhancing safety features based on actual driving conditions.

3. Digital twins streamline production and supply chains

Toyota has embraced digital twin technology to enhance visibility and efficiency across its supply chain. By creating virtual replicas of its European manufacturing plants, Toyota can simulate and plan changes to production lines without disrupting actual operations. This approach allows for better analysis of inventory levels, transport routes, and potential bottlenecks, leading to more informed decision-making.

The integration of digital twins has enabled Toyota to respond more swiftly to market changes and reduce the risk of costly delays. For instance, by analyzing real-time data from these virtual models, Toyota can identify inefficiencies and adjust production schedules accordingly. This proactive approach has proven particularly valuable during periods of uncertainty, such as the COVID-19 pandemic, where traditional methods of planning and forecasting were challenged.

Furthermore, Toyota's use of digital twins extends beyond production lines to encompass the entire supply chain. By simulating various scenarios and outcomes, Toyota can anticipate potential disruptions and develop strategies to mitigate them.

This level of foresight and agility has strengthened Toyota's ability to maintain continuity and meet customer demands, even in the face of global challenges. In fact, during this time, Toyota reported a reduction in lead times due to its ability to leverage digital twins for more agile decision-making.

Toyota’s approach highlights how real-time visibility transforms decision-making. enhancing supply chain resilience and efficiency.

By creating virtual replicas of vehicles, production lines, and supply chains, manufacturers can anticipate problems, optimize processes, and make smarter decisions across the lifecycle. Real-world benefits include:

1. Improved quality control: Real-time monitoring through digital twins allows manufacturers to catch defects before vehicles leave the production line, ensuring higher-quality output and reducing costly errors.

2. Proactive maintenance: Predictive analytics make maintenance proactive rather than reactive. General Motors, for example, uses digital twins to simulate production lines before construction, optimizing planning, scaling faster, and tracking component health to schedule repairs before failures occur.

3. Cost reduction and sustainability: Digital twins help cut costs and support sustainability goals. Remote monitoring minimizes waste, optimizes energy use, and allows process improvements without sending teams to the factory floor.

4. Safe and effective training: Engineers can train with interactive simulations, gaining hands-on experience safely before handling physical machinery.

5. Lifecycle insights and market responsiveness: Because data flows across the product lifecycle, manufacturers gain insights into performance, customer usage patterns, and market demand, enabling more effective vehicle customization.

6. Enhanced maintenance and aftermarket services: Digital twins enable predictive diagnostics, allowing dealers to address issues before breakdowns occur. Consumers benefit from personalized software updates, optimized parts replacement, and mechanics can rehearse complex repairs in simulation, all while remote monitoring supports seamless over-the-air updates.

S&P Global Mobility’s AutoTechInsight platform provides automakers with the technology data and supply chain intelligence needed to make informed decisions and investments in innovations like digital twins. Our datasets — covering 15 vehicle domains, regulatory trends, and supply chain dynamics — enable manufacturers to model production scenarios, plan technology rollouts, and reduce operational risks.

We deliver integrated data that connects teams, breaks down silos, and supports faster, more effective adoption of innovative automotive technologies.

Learn more about our AutoTechInsight platform and access the intelligence that supports smarter decisions and measurable value from day one.