Tata Consultancy Services (TCS) introduced its latest research study, titled the “Digital Twindex Report for Future-Ready Mobility 2026,” at CES 2026 in Las Vegas. The report captures a noticeable shift taking place across the automotive industry. Artificial intelligence (AI) and digital twins, once mainly used behind the scenes for design and testing, are now actively operating within vehicles and factories, learning continuously and responding in real time.
What stands out, perhaps more than anything, is that this intelligence is no longer confined to early development stages. It is increasingly embedded into everyday mobility systems, often quietly, but with growing impact.
Key Takeaways
- Intelligence on the Road: Smart technologies are moving beyond simulations and prototypes into real-world driving environments, improving vehicle safety and reliability in practical, measurable ways.
- Adaptive Manufacturing: Factories are evolving into learning systems. Using AI, they can detect issues as they emerge and adjust operations automatically, rather than waiting for manual intervention.
- Physical AI: Vehicles are becoming what the report describes as “Physical AI assets.” They connect to broader data networks, learn from fleet-wide experiences, and improve continuously over time.
- Cognitive Supply Chains: Supply networks are using digital twins to make quicker, more informed decisions, strengthening resilience against disruptions that have become increasingly common.
From Design to Real-World Action
For a long time, digital twins, virtual replicas of physical systems, were largely confined to engineering labs. They helped teams design vehicles, test scenarios, and identify flaws before production began. The TCS report suggests that this role has expanded significantly.
Intelligence is now embedded directly into vehicles on the road and into the factories assembling them. Cars can learn from the collective experiences of an entire fleet. If one vehicle encounters a safety issue or unusual condition, that insight can be shared and applied across similar vehicles. This idea, known as “Physical AI,” effectively transforms cars from static products into connected assets that evolve over time.
Anupam Singhal, President of Manufacturing at TCS, emphasized that most drivers may never notice these changes directly. “For most people, mobility is about trust,” Singhal said. “What is changing is how intelligence is being woven into vehicles, factories, and mobility ecosystems to support that trust, often without being noticed.”
Factories That “Think”
Manufacturing itself is undergoing a parallel transformation. According to the report, factories are no longer just executing fixed instructions. Instead, they are gaining cognitive capabilities through sensors, feedback loops, and AI-driven decision systems.
These plants monitor their own performance continuously. When something drifts off course, whether related to quality, efficiency, or throughput, they can adjust operations dynamically. In some ways, it resembles how a living system responds to its environment, adapting rather than reacting too late.
Ajay Wadhwa, CEO of Tata Motors Global Services Limited, pointed out how quickly this shift has taken place. He observed that while the industry experienced relatively gradual change for many years, the pace of innovation in the last few years has accelerated sharply and is set to redefine how companies operate.
Managing Complexity
The automotive ecosystem remains deeply complex. It includes vehicle manufacturers, suppliers, software platforms, and digital infrastructure, all operating across different regions and timelines. Matt McLarty, Chief Technology Officer at Boomi, noted that this complexity is not disappearing.
Instead, the challenge is learning how to connect these layers so they can share intelligence smoothly. According to the report, success will depend on how well companies can orchestrate data across the supply chain without adding unnecessary operational burden or fragmentation.
TCS and the Future of AI
This report launch also reflects TCS’s broader ambition to become the largest AI-led technology services company worldwide. By helping clients move beyond pilot programs into large-scale deployment, TCS aims to turn advanced technologies into practical, repeatable outcomes.
This is the first Digital Twindex edition to focus specifically on mobility. It builds on earlier reports that examined Manufacturing, Sustainability, and Healthcare. Those earlier studies focused on laying the groundwork for AI adoption. This latest report shows how that groundwork is now delivering tangible results, particularly within the automotive sector.
Frequently Asked Questions (FAQs)
Q1: What is the TCS Digital Twindex?
A1: The TCS Digital Twindex is a series of research reports that track how industries adopt digital twin technology and AI. It measures how these tools influence business performance and operational outcomes.
Q2: What is a Digital Twin in this context?
A2: A digital twin is a virtual representation of a physical asset, such as a vehicle or factory machine. In mobility, it helps organizations monitor real-time conditions or predict maintenance needs before failures occur.
Q3: How does “Physical AI” make cars safer?
A3: Physical AI allows vehicles to sense their surroundings and learn from data gathered by other vehicles. This shared learning enables better decision-making, improving overall safety and reliability for passengers.
Q4: Why is this report important for the average person?
A4: It suggests that future vehicles will become more dependable and safer over time, as they can update and improve themselves in ways similar to modern software updates.
Q5: Is this technology available now?
A5: Yes. The report indicates that many of these technologies are moving beyond experimental stages and are already being deployed at operational scale in real-world environments.
