Over the past few years, AI has reshaped how we interact with the digital world. Now, it is moving beyond the screen and into the physical world. This is not just an evolution. It is an architectural shift, one that will define the next wave of innovation.
Most conversations around AI tend to focus on language models, their fluency, reasoning, and occasional inaccuracies. But that lens overlooks a far more demanding frontier. Physical AI goes beyond generating responses. It refers to systems that act. They sense, move, and interact with the real world, powered by sensors, robotics, and real-time decision-making. The shift here is not incremental. It is fundamental.
In digital systems, small errors can possibly be corrected. In physical systems, they cannot. A minor misalignment in a robot can damage a component. A disrupted navigation signal can lead to critical failure. The expectations, therefore, are far higher. Quality, reliability, and repeatability are non-negotiable.
Physical AI operates quietly in the background, embedded within machines and systems, acting on the world rather than merely interpreting it. You see it in manufacturing processes that achieve micron-level precision, in systems that navigate GPS-denied environments without drift, and in technologies that detect faults before they become visible. and so on. This is physical AI in action.
India’s position in physical AI is shaped by several forces coming together. The country is moving from supporting global innovation to actively shaping it, contributing to a full-cycle environment. Over the years, many GCCs in India have evolved from execution arms into centres that originate product architecture, own technical design, and in some cases solve end-to-end business problems At the same time, a few global companies are expanding both engineering and manufacturing footprints in India. This makes it a base not just for development, but for piloting and scaling solutions in real-world environments, enabling faster iteration and stronger reliability.
Engineers are trained in fundamental disciplines like physics and AI side by side creating a strong foundation for building physical AI systems, where software must interact seamlessly with the real world. Leading institutions like IISc are advancing research in robotics and intelligent systems with a clear focus on real-world applications. At the same time, teams across the country are building core technologies such as sensor fusion, spatial intelligence, and real-time autonomy frameworks.
The progress is driven by a tightly connected ecosystem of corporates, academia, and startups. Academic institutions are generating deep technical knowledge. Enterprises are scaling and deploying solutions. Startups are bridging the gaps and translating research into real-world applications at speed. This interplay is critical. It helps accelerate both speed and reliability.
As physical AI continues to evolve, R&D in India is not just supporting this journey, it is actively shaping its direction. This shift is already visible in the work being driven at Hexagon R&D India.
Systems that once followed predefined rules are becoming adaptive and intelligent. On factory floors, precision measurement is moving beyond inspection. It is learning from data, identifying patterns, and detecting what is not immediately visible. The focus is shifting from defect detection to defect prevention, enabling first time right by design.
At the core of this transformation is the digital twin, the live computational mirror of a physical system. Built by R&D teams in India, these models use near real time data to simulate, predict, and optimise. They are turning systems into continuously learning environments.
The impact is extending beyond typical industry. In medical aesthetics, solutions like AURA by Hexagon are creating high fidelity 3D digital twins of the human face, enabling a new level of precision and personalisation. At companies like Hexagon, a part of this work is being done from India as a core contributor shaping the foundations of physical AI for real-world systems.
The writer is head and SVP, Hexagon R&D India.
Disclaimer: The views expressed are the author’s own and do not reflect the official policy or position of Financial Express.