The Rise of Physical AI: When Intelligence Enters the Real World

By Navot Goren

January 27, 2026

Artificial Intelligence has largely lived in the digital realm, analyzing text, images, speech, and data streams inside servers, clouds, and devices. A new phase is now emerging: Physical AI. Physical AI extends intelligence beyond perception and reasoning into action, enabling machines to sense, decide, and interact with the physical world in real-time.

From robots and autonomous machines to smart infrastructure and industrial systems, Physical AI represents the convergence of AI, sensing, actuation, and connectivity. It is not just about being smart – it is about being present, responsive, and aware in the real world.

Physical AI refers to AI systems that are embodied in physical entities, machines that can perceive their environment, understand context, and take real-world actions. Unlike purely digital AI, Physical AI operates under real-world constraints, including time-critical decision making, strict safety and reliability requirements, and continuous interaction with humans and dynamic environments.

The market for Physical AI is entering a period of unprecedented growth. Industry analysts project the global market to reach a multi-billion-dollar valuation within the next few years, maintaining a robust compound annual growth rate (CAGR) exceeding 30%. This surge is driven by the transition of humanoid robots from research laboratories to active factory pilots. Today, pioneering companies such as Tesla, Figure, and Agility Robotics are leading the charge, proving that embodied intelligence is no longer a futuristic concept but a looming industrial reality.

Physical AI is becoming viable due to the convergence of three forces: powerful edge AI processors capable of real-time inference, advanced sensing technologies, and next-generation wireless connectivity. Together, they enable intelligent systems that can perceive, decide, and act locally, while still leveraging cloud-scale intelligence when needed.

Physical AI relies on a continuous feedback loop between local intelligence at the edge and shared intelligence in the cloud. While critical decisions must be made locally and in real-time, connectivity enables learning, coordination, and system-level optimization across fleets of devices.

Wi-Fi 7: Enhancing Latency and Throughput

Wi-Fi 7 improves latency significantly, achieving sub-2 milliseconds latency in optimized conditions, while supporting peak theoretical speeds over 40 Gbps. This allows Physical AI devices to transfer high-throughput data in relatively low latency between the system and the internet, crucial for applications like edge AI processing in robotics or real-time sensor data analysis. Features like Multi-Link Operation (MLO) reduce jitter and improve reliability in dense environments, making it ideal for industrial automation.

Bluetooth, Particularly Bluetooth 7.0 with HDT

Bluetooth has traditionally been associated with low-power, short-range communication, but Bluetooth 7.0 changes this perception by introducing High Data Throughput (HDT) capabilities that support data rates of up to 7.5 Mbps. This level of performance allows Bluetooth to serve as a practical alternative to physical cables in Physical AI systems, especially those involving motion. By removing heavy and fragile wiring, Bluetooth HDT improves mechanical reliability and enables greater freedom of movement in robots and other mobile platforms. It also supports modular and serviceable system designs, where sensors, controllers, and actuators can be connected wirelessly without compromising robustness.

Ultra-Wideband (UWB): Speed and Spatial Awareness

UWB can deliver extremely low-latency, high-bandwidth data at short range, in some cases comparable to or exceeding Wi-Fi, while also providing precise spatial awareness accurate to centimeters, even in Non-Line-of-Sight (NLoS) scenarios. This combination is critical for Physical AI mobility, as UWB can function like radar to detect obstacles and enable navigation in challenging environments, outperforming cameras in low-visibility or cluttered settings. UWB’s integration in robotics boosts safety and efficiency by allowing autonomous systems to accurately track positions, avoid collisions, and collaborate seamlessly.

Companies like Ceva play a critical role in this transformation by providing the foundational Silicon IP that blends high-performance Edge AI acceleration with multi-standard wireless connectivity. By enabling Wi-Fi 7, Bluetooth 7.0, and UWB alongside efficient on-device processing through the “Connect, Sense, Infer” framework, Ceva allows Physical AI systems to be intelligent, mobile, and power-efficient by design. Ceva’s IP acts as the “invisible engine” inside the chips, ensuring these machines interact with the world safely, autonomously, and in real-time.

Physical AI is not just a technological trend; it’s a transformative force reshaping how we live and work. By addressing real-world challenges with intelligent, adaptive systems, it promises a future of enhanced productivity, safety, and innovation. As the market surges and connectivity evolves, Physical AI will increasingly integrate into everyday life, from smart factories to autonomous homes. The journey has just begun, but its potential is boundless.