Physical AI is transforming every industry, from manufacturing, where robots are already critical to factory lines that assemble devices, to agriculture, where autonomous tractors can till crops and use imaging data to harvest when ready. In retail settings, robots scan grocery aisles daily to give accurate updated inventory and restock shelves overnight. Meanwhile, the logistics industry has introduced robots that are able to retrieve, sort and package items for efficient and safe handling. The automotive industry continues to leverage Physical AI to move from driver-assisted cars to fully autonomous fleets that can be updated remotely.
Now we face a key question: Do people trust physical AI? Only with trust can these futuristic capabilities become the norm rather than interesting use cases.
Why we’re entering a new paradigm in robotics
This world is possible because the physical AI learning curve continues to bend toward faster, better and cheaper developments. Synthetic training environments have become a less costly and less risky alternative to expensive physical experimentation while accelerating improvements. For example, Boston Dynamics’ Spot robot has achieved 87% accuracy in detecting objects in simulation, thanks to the help of synthetic training data from NVIDIA’s Isaac Sim and Replicator. More companies are also turning to simulated environments for competitive advantage; for example, BMW invested €2 billion into a factory powered by a digital twin, aiming to accelerate development and improve planning efficiency by 30%.
Robotics developers, on even the smallest teams, increasingly have access to rich physical world data thanks to world foundation models (WFMs), which offer an advanced starting point for new capabilities. Early pioneers like Figure AI and Agility Robotics are already demonstrating how well physical AI can integrate into different human environments. Major advances are happening in robotics software too: Orchestration models such as DeepMind’s AutoRT have demonstrated how to control fleets of robots across different tasks with limited human intervention. In Europe, fleets of miniature robots are being trialed to help with search and rescue operations, navigating through collapsed buildings and piles of rubble to find people trapped underneath.
