Physical AI: The Next Wave of AI Development

This article is part of interviews with Linda Yao, Vice President and General Manager of Hybrid Cloud & AI Solutions at Lenovo, and Michael Benisch, Vice President of AI at Motive. These interviews were conducted for Tech.co’s AI newsletter, The AI Strat. For more interviews with AI experts on the latest trending topics, subscribe to the newsletter here. 

Undoubtedly, AI has developed fast. But, so far, progress has been mostly confined to a laptop or smartphone screen. Chatbots and agents are more powerful than before, workflows can be fused with AI for stronger efficiency, and so on.

On the physical side, progress has been slower, which isn’t unusual for an industry that usually takes a longer to integrate new technologies.

Despite this slower pace, physical AI is still changing the way businesses are operating. AI within warehouses and transportation has developed substantially, increasing productivity across the board. But experts say physical AI has benefits beyond productivity, potentially making whole industries and professions safer for human operators.

I spoke to Linda Yao, Vice President and General Manager for Hybrid Cloud and AI Solutions at Lenovo, and Michael Benisch, Vice President of AI at Motive, to see where industries are at now with physical AI and what we can expect for the future.

Physical AI Has Been Slower to Develop

In a 2025 keynote, NVIDIA CEO Jensen Huang claimed: “The next frontier of AI is physical AI.” When I first start talking with Michael Benisch, VP of AI at fleet management solutions provider Motive, he uses similar language to talk about physical AI, calling it “one of the last frontiers,” that needs to be unlocked in the AI world.

Benisch has been working on physical AI for almost a decade. His resume includes the self-driving division at Lyft, as well as stints at Toyota and General Motors.

“When people think about AI, it’s usually the chatbots we talk to on the web or if you use Claude Code or something like that,” he says. “But then there’s the other half of the world out there, where you need to get your packages from Amazon, and you need to get your real food.”

When I asked him why progress was generally slower, he said there are a lot more obstacles you can’t overcome, when you’re dealing with the physical world. Unlike computer programs, issues can’t be fixed by “simply hacking through it in a weekend.”

How Organizations Have Been Adopting Physical AI

Plenty of companies are already seeing massive gains with physical AI. Linda Yao, VP and General Manager of Hybrid Cloud & AI Solutions at Lenovo, helps organizations adapt to emerging technologies. At one point, this was hybrid cloud, and now it’s AI.

One company, ST Logistics, wanted to, in Yao’s words, “automate as much of their warehouse as possible.” The formula for this case was physical plus digital AI, Yao explains. On the physical side, this includes robots, and they sound like the kind of robots you’d expect in a typical sci-fi movie.

One robot helps “efficiently move the equipment or move the inventory from one side of the dock into the receiving inventory warehouse,” and another does “the physical loading and unloading.” Then, there is another robot that is more “detailed,” it identifies the right boxes and stacks them in the right order.

For the digital side, Yao explains: “We are working to make sure that the systems being used, the IT systems being used to log the inventory, to track the data, to take the orders, to make sure that the orders are shipped on time. That’s all then connected back into not just the human workflow, but also the robot workflow and the AI workflow.”

Overall, Yao says ST Logistics reduced order processing time by 40%, reduced energy consumption by 30%, and increased productivity by 30%. “It really is bringing together the physical as well as the digital, as well as the human element to make this AI solution work.”

Physical AI Can Make Physical Professions Safer

Yao describes the kind of work going on in warehouses as “backbreaking,” particularly for workers that are loading and unloading, or spending an hour in cargo containers that can get to 120 degrees Fahrenheit in the summer. A lot of the time, she says, companies are struggling to find people who even want to do that work.

This obviously makes the logistics industry a prime candidate for AI. Especially since trucking is considered one of the most dangerous careers out there: according to the US Bureau of Labor Statistics, almost 800 truck drivers lost their lives in a work-related incident in 2024.

Motive’s suite of AI-powered products offer increased safety for drivers out on the road, Benisch tells me. One company, Agmark, adopted Motive’s AI dash cams, and as a result, saw a 67% reduction in accidents and a 15% reduction in unsafe driving behaviors. 

Similarly, chilled products distributor Damian’s Enterprises saw a 20% improvement in safety scores when they adopted Motive’s AI Dual-facing dash cams.

Improving safety, Benisch explains, is one of the ways fleet operators and managers can get their drivers behind them when AI is implemented. He encourages leaders to tell their team, “You have the ability now to do a better job than you did before. You can be safer. You’re more likely to come home at the end of the shift.”

What’s Next in the Physical AI Space?

At the end of our interview, I asked Benisch for his physical AI predictions in the next year. A question I sometimes feel cruel for asking, especially since one year’s progress can take place in a few days with AI.

“Physical AI isn’t moving as fast as the other AI areas… it’s not like the rocket ship growth that you see from ChatGPT or Claude Code,” he says. He does predict, however, “there will be market differences and things that are hugely improved.” Within the driving space, he predicts “the passenger space will be more and more automated, but taxis will still be there, and Lyft and Uber will still have human drivers.”

Like Benisch, other experts say the same about human contribution within the physical AI space.

“Between now and 2040, I certainly expect robotics and physical AI to create at least a trillion dollars in economic value, most of that in manufacturing and logistics. That will happen not through worker replacement and productivity but through our ability to innovate what products we make, how we make them, and what tasks humans perform versus which ones are automated, elevating the nature of work for humans to more problem-solving and to sort of a catcher role, rather than just relying on our physical dexterity.” — Ani Kelkar, in an article for McKinsey & Company

While we’ll certainly see the most gains from physical AI within logistics and manufacturing, this could lead to physical AI developments across other industries. Bloomberg reported earlier this month that OpenAI are planning to release their first hardware device, a screenless speaker with integrated AI capabilities.

The design of the product is still currently under development, but is being pitched internally as a “humanlike AI companion that lives in the home.” Though fascinating, I think most would prefer a robot that carried groceries from the store.