Artificial intelligence alone will not define the future of commercial vehicles, which will instead depend on combining AI with engineering and domain expertise, according to Radhakrishnan Kodakkal, Managing Director and CEO, Daimler Truck Innovation Center India.
Speaking at Siemens Realize LIVE APAC 2026, Kodakkal said the next generation of commercial vehicles will be defined not by AI alone, but by the ability to combine digital intelligence with domain expertise across the entire product lifecycle.
“The future belongs to organisations that can combine domain expertise with digital intelligence,” he said.
Commercial Vehicles Are Becoming Software-Defined Products
Kodakkal said commercial vehicles are increasingly becoming software-defined products that continue to evolve long after they leave the factory. Commercial vehicles typically remain in operation for 10 to 14 years, or even longer, making continuous software upgrades, cybersecurity updates, and new digital features essential throughout their lifecycle.
Why AI and Data Alone Can't Deliver Predictive Maintenance
He said connected vehicles, digital twins, and AI-driven analytics are enabling manufacturers to move beyond scheduled servicing towards condition-based and predictive maintenance. Instead of simply alerting drivers after a failure occurs, future systems will be able to diagnose issues remotely, determine their severity, and recommend the most appropriate course of action, whether that is continuing the journey, visiting the next workshop, or dispatching a service vehicle.
According to Kodakkal, however, data and AI alone cannot deliver such capabilities.
“It is not just the data and AI. The real difference comes from combining real-world data with domain expertise,” he said, adding that understanding vehicle physics, customer applications, and operating environments is critical to developing meaningful digital solutions.
Digital Twins Set to Reshape Commercial Vehicle Development
He also stressed the growing importance of integrated digital twins in product development. By bringing together requirements engineering, design, simulation, manufacturing, and validation into a single digital workflow, manufacturers can identify issues much earlier, reduce physical prototyping, and shorten development cycles.
Kodakkal argued that manufacturing simulation should begin during the design stage itself, since manufacturing processes often influence product design decisions. Advances in photorealistic rendering, augmented reality, and virtual reality are also allowing OEMs to validate products with customers even before the first physical prototype is built.
The Road Ahead: Daimler's Formula for Future Trucks
Looking ahead, he said organisations must build the capability to rapidly adopt emerging technologies while responding to changing regulations, customer expectations, and geopolitical developments.
For commercial vehicle manufacturers, he said, the winning formula will be a combination of software-defined engineering, AI-enabled digital intelligence, simulation-driven development, and deep domain expertise, rather than reliance on AI alone.