Industrial Automation is Advancing with AI, and the Opportunity is Huge

April 30, 2026

Story

Ever since Physical AI became the hype term of the day, it’s rubbed me a bit wrong.

As it’s commonly defined, physical AI describes the intersection of AI with the physical world and the compute process by which AI can sense, control, and act in the real world.

These decisions and actions are made based upon sensor data (Read: Sensor Fusion), and statistical analysis of historical models and training against data (Read: Machine Learning & AI). All of this leads to commands sent to robotics, control systems, valves, actuators, and all the rest of the devices at the edge.

All-in, that’s the so-dubbed “Physical AI,” and that’s well enough, I suppose, but my problem boils down to this: we already have a better term for that process and all of the underlying technology. That is the heart of what Embedded Computing is and has been. Well-designed compute structure and function, embedded within the physical devices that will act. It’s a relatively recent addition to the embedded computing sphere that physical AI is claiming as a differentiator, however, it’s still been a part of embedded since its inception: Industrial Automation.

And there’s the rub, isn’t it? Industrial Automation is in a boom cycle like we rarely see. Price Waterhouse Cooper (PwC) predicted in a February 2026 report on the state of Industrial Automation, “The median share of industrial manufacturers that will have highly automated processes is expected to more than double – rising from 18 percent to 50 percent,” by 2030, and that’s a huge jump in a short time. What’s more, the companies that are leading the way now are likely to expand their lead as competitors try to catch up.

Ryan Hawk, Global Industrials and Services Leader, PwC US, said, “As tech adoption and automation accelerate, advantage will shift from who has tools to who can adopt them and orchestrate them the fastest. Agile, tech-enabled, and future-fit manufacturers already have an edge – with the divide between those who are tech-enabled and those still operating with patched up systems to widen even further.”

Now, PwC has also looked at physical AI, and, in fairness, the firm doesn’t see it like I do. However, if you accept my premise that physical AI is just another term for embedded computing (and I do), the future is also bright for the embedded companies leading the way on automation.

PwC, in this report from March 2026, predicts that the global Physical AI market could reach nearly $500 billion by 2030, and the next 3 to 5 years will see early pilots scaled to  commercial deployment in constrained domains and early adopter use cases. Most tellingly, and exciting to me, is that the report foresees value accruing across the entire ecosystem, so benefits and growth are not likely to be restricted to robotics and vehicle manufacturers, but also “semiconductor suppliers, cloud and data center operators, simulation and software platform providers, infrastructure players, and end users who redesign processes around embodied intelligence.”

In a recent piece, Rich Nass, contributing editor of Embedded Computing Design, writes about the critical intersection of motor control and physical AI. This is emblematic of the entire physical AI trend. Every part of it is dependent upon and deeply entwined with embedded technology and industrial automation innovation.

As 2026 continues, look for those intersections between the physical and the digital, between the AI and the servo motor, and between the embedded computing and the machine learning. You’ll see that there’s a lot to see.