Physical AI surges, sparking a rush to claim a stake

A distinct momentum is building in the technology industry—not from a single breakthrough, but from the simultaneous convergence of many. Physical AI is experiencing that moment right now. Understanding where it comes from and why reveals more than any individual product launch could.

Physical AI is a straightforward term. It refers to AI systems that do more than process data or generate content—they perceive, reason, and act in the real world: robots, autonomous vehicles, adaptive machines. Nvidia CEO Jensen Huang described it as “the ChatGPT moment for robotics” at CES in January—a deliberate and helpful framing.

The ChatGPT comparison is not about hype. It signals that a technology once limited to research labs is now ready for mainstream commercial adoption. That transition is exactly what we are witnessing, from factory floors in Silicon Valley to stages in Shanghai.

The West Builds the Stack

On the Western side, the physical AI push is fundamentally a platform race. The most aggressive investors are not primarily robotics companies—they are infrastructure companies that see robotics as the next surface for AI monetisation.

Nvidia has released new Cosmos and GR00T open models for robot learning and reasoning, alongside the Blackwell-powered Jetson T4000 module, which delivers 4x greater energy efficiency for robotics computing.

Arm has carved out an entirely new Physical AI business unit focused on semiconductor design for robotics and intelligent vehicles.

Siemens and Nvidia announced plans to build what they call an Industrial AI Operating System, aiming to create the world’s first fully AI-driven adaptive manufacturing site.

Then there’s Google, which last week brought its robotics software unit Intrinsic fully in-house—moving it from Alphabet’s “Other Bets” into Google’s core.

This move positions Google to offer manufacturers a vertically integrated stack: AI models from DeepMind, deployment software from Intrinsic, and cloud infrastructure from Google Cloud. The Android analogy being floated internally is instructive. Android didn’t win smartphones by building the best phone; it won by becoming the layer everything else ran on.

That is exactly what Google is attempting with physical AI.

The enterprise implications are significant. A Deloitte survey of more than 3,200 global business leaders found that 58% are already using physical AI in some capacity, rising to 80% with plans over the next two years. The demand is there. The question has shifted from whether to adopt to how fast and on whose platform.

Eastern Companies Build the Machines

China’s physical AI story is different in character—and arguably more visceral. At this year’s Spring Festival Gala, humanoid robots from multiple Chinese startups performed kung fu routines, aerial flips, and choreographed dances before hundreds of millions of viewers—a stark contrast to the stumbling prototypes that drew skepticism just a year earlier.

It was a spectacle, yes. But it was also a statement. China accounted for over 80% of global humanoid robot installations in 2025 and over half of the world’s industrial robots. That dominance is underpinned by structural advantages that go beyond software. China controls roughly 70% of the global lidar sensor market, leads in harmonic reducer production—the gears critical to robot movement—and has driven hardware costs down through the same economies of scale that propelled its EV industry.

Alibaba has entered the race with RynnBrain, an open-source AI model designed to help robots comprehend the physical world and identify objects—positioning itself alongside NVIDIA’s Cosmos and Google DeepMind’s Gemini Robotics in the foundation model layer. With over 140 domestic humanoid manufacturers and more than 330 humanoid models already unveiled, China’s push into embodied AI is no longer experimental—it’s commercial.

Why This Matters Beyond the Headlines

The convergence of Western platform strategies and Eastern manufacturing scale is creating something genuinely new: a global physical AI ecosystem that advances on multiple fronts simultaneously, with different competitive advantages colliding.

What makes this moment distinct from prior robotics waves is the removal of the expertise bottleneck. Historically, deploying industrial robots required specialized engineering teams, months of custom programming, and a high tolerance for downtime. The platforms being built now—by Google, Nvidia, Siemens, and their Chinese equivalents—are explicitly designed to lower that barrier.

Companies like Vention, which raised US$110 million in January, claim their physical AI platforms can reduce automation project timelines from months to days. When that claim becomes routine, the economics of manufacturing change structurally.

There is also a geopolitical dimension that sits quietly beneath the product announcements. Every foundation model for robotics, every platform layer, every semiconductor architecture being developed now carries with it questions of supply chain dependency, data sovereignty, and long-term infrastructure control.

The country—or company—that governs the software layer of physical AI will have unusual leverage over industrial operations globally for years to come.

Physical AI is not a trend. It is the next significant reconfiguration of how the world makes things, moves things, and operates at scale. The conversations happening now—from semiconductor boardrooms to factory floors in Shenzhen and Silicon Valley—are not preliminary. They are the thing itself, already underway.

See also: Goldman Sachs and Deutsche Bank Test Agentic AI for Trade Surveillance

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