One particular section caught my eye that was unexpected:
“Expect physical AI to be on the tech buzzword list this year. The term refers to applications where AI takes on a physical form, from robotics to driverless cars. My own experience at Davos highlighted just how real this push has become: one evening at dinner, a robot was sitting right at the table.
“EY’s Sharma labeled physical AI the ‘next wave,’ estimating it could be five to six times the market size of agentic AI within five to six years.
“Meanwhile, Sassine Ghazi, CEO of semiconductor design tool company Synopsys, said he initially expected physical AI would come ‘five plus’ years down the road, but it is coming ‘much faster.’”
So here we are in late March, and I am returning to this topic, as I prepare to head to the RSA Conference in San Francisco.
WHAT IS PHYSICAL AI?
Here are some definitions, examples and implications from various sources:
IBM: “What is physical AI?” — “Physical AI refers to artificial intelligence (AI) systems that operate in and interact with the physical world, rather than existing only in software or digital environments.
“Physical AI typically involves the combination of AI models with sensors, actuators and other control systems that allow models to act upon real-world environments, taking models from the realm of bits to the realm of atoms. With AI, advanced physical systems can now perceive the environment, reason with the power of a large language model (LLM), act accordingly, and then learn from the outcome of that action.”
NVIDIA: “What is Physical AI?” — “Physical AI lets autonomous systems like cameras, robots, and self-driving cars perceive, understand, reason, and perform or orchestrate complex actions in the physical world. …
“Previously, autonomous machines were unable to perceive and sense the world around them. But with physical AI, robots can be built and trained to seamlessly interact with and adapt to their surroundings in the real world.”
Global X: “Robotics & Physical AI: A New Era in Automation” — “Robotics elevates AI from the digital realm into the operating system of the physical world. As generative AI models grow more capable and associated hardware becomes cheaper and more versatile, we’re rapidly advancing into the era of Physical AI, where networks of machines can think, see, move, and act in real time to augment human workflows.
“This shift carries profound implications. Human labor productivity could be supercharged as people increasingly deploy robots for physical tasks. Entirely new use cases will emerge across sectors such as last-mile logistics, self-driving, and robotic manufacturing. Ultimately, this could culminate in Humanoid systems advancing, as general-purpose physical AI brings intelligent automation to everyday businesses and households. In our view, Robotics & Physical AI form a defining theme of the intelligence age.”
Citigroup.com: “Embodied Intelligence: The Rise of Physical AI” — “We see Physical AI as at an inflection point, with abundant capital, maturing technology and a diversifying ecosystem. AI-enabled edge devices (those at the ‘edge’ of a network as opposed to the central data center or cloud) could see growth in double-digit percentages, as could design and simulation software. …
“In recent years, AI investment for industrial names has been dominated by the impact of Generative AI (GenAI) and LLMs on data centers and related infrastructure. Physical AI is different in that it’s domain specific, requiring separate adoption by end markets that each have unique requirements. That means spending patterns will be defined not by hyperscalers’ capex plans, but by the pace of adoption in each end market.
“We see three pillars of success for industrial companies: digital twin models (which are virtual representations of physical processes), real-world data gathering through edge devices, and simulation. We’re at the beginning of this journey, as development of the technology is nascent and the industrial cycle will play a role. But companies are already preparing for what’s coming, and we expect investment to continue to pivot to Physical AI adoption.”
MORE IMPLICATIONS OF PHYSICAL AI
Consider these deeper-dive stories on physical AI:
IBM: “What is physical AI?” — “Several bottlenecks that previously prevented a physical AI revolution are being broken at the same time. The first and most important is the arrival of generative AI, powered by foundation models. Today’s large computer vision and multimodal models can recognize objects, understand spatial relationships and generalize across settings. This reduces the amount of specific training required for individual tasks and allows systems to re-use intelligence across them.
“The second challenge is now being overcome by the power of modern simulation, which combines high-fidelity physics modelling, photorealistic rendering and parallelization. This dramatically reduces model training times and makes simulation useful not just for testing but as a primary training ground. A related trend is the explosion of compute availability. Breakthroughs in GPUs and data centers have made training at scale feasible.
“Finally, hardware is better than ever. Modern robots have better sensors and lighter materials. They can take advantage of recent edge AI breakthroughs and better communications capabilities. These innovations have made experimentation viable, even for small startups. The result is a renaissance for physical automation initiatives, from autonomous vehicles to industrial robots and healthcare bots that perform surgery and other complicated procedures.”
Fierce Network: “LoRaWAN takes IoT to the physical AI realm”— “It might sound strange that a low-power IoT technology like LoRaWAN is angling to become the perfect partner for power-hungry AI, but that’s exactly how the LoRaWAN Alliance is framing it.
“‘The next thing for AI is to get its hands on the physical world and for that, it needs to start sensing the physical world and commanding that,’ LoRa Alliance CEO Alper Yegin told Fierce. ‘We are in the best position to be the main connection between the physical world and the AI.’
“With more than 10 years behind its foundation as an IoT specification, LoRaWAN certainly enjoys a robust ecosystem. More than 625 devices are certified and more than 125 million LoRaWAN devices are deployed globally, boasting a 25 percent compound annual growth rate.”
Nikkei Asia: “Physical AI to impact 41% of companies in 3 years, Deloitte says”— “Physical AI is all the buzz in 2026, but just 3 percent of companies surveyed by Deloitte have extensively integrated it into their operations, according to a new white paper. But four out of 10 see it having a transformative impact within three years.”
FINAL THOUGHTS
So are states ready for this new world with a new “AI economy”?
The simple answer is no, according to one report, The AI Maturity Matrix by BCG, which reads, “Economic and workforce-development leaders throughout the US are in broad agreement on the importance of AI: 88 percent of them see the technology as crucial to the competitiveness of their economies. But fewer than 10 percent say their state has a well-defined strategy in place for responding to AI’s economic impact.”
The report offers numerous suggestions around physical AI, as well as other areas of AI development.
