The hidden value of physical AI

Ani Kelkar (0:02)

If I reach for a cup and discover it is heavier than what I thought it needs to be, I change my grip. If someone walks into my path, I change direction. I anticipate how the world around me will respond to my actions and I prepare for it. And if we start imbuing these capabilities into what a machine can do, it can start manipulating irregular objects.

Lucia Rahilly (0:24)

That's McKinsey partner Ani Kelkar. He's talking about the growing sophistication of physical AI. Ani joins me and McKinsey senior partner Mark Patel to discuss the ways advances in physical AI are generating new value and reshaping the future of work. This is The McKinsey Podcast, where we help you make sense out of the world's toughest business challenges. I'm your host for today, Lucia Rahilly.

Let's start with some context. What exactly do we mean when we talk about physical AI and why is it generating so much buzz?

Mark Patel (1:04)

We're obviously living in a moment where generative AI is transforming many aspects of how we experience the digital world. When we talk about physical AI, we're moving from digital outputs, text, code, images, to the physical, the real assets, real spaces, real places, real operations.

If you want, you can think of physical AI as in the same way that generative AI, a couple of years ago started with us using LLMs and enabling chatbots. That's really evolved. We don't experience generative AI just as a chatbot. Now, we experience it in many different forms. It's in the form of code generation, in the form of image recognition and generation, in the form of engineering design, the processes that are getting accelerated, drug discovery, all of these applications that we see the large language models being applied to. But just as we've seen that the generative ball ball, we expect the same with physical AI. It's going to look like autonomous systems in the form of autonomous vehicles, industrial equipment, industrial operations that will be more autonomous, warehouses, drones, medical systems, all kinds of infrastructure.

Lucia Rahilly (2:17)

Let's turn to you to talk about the economic picture. We certainly spend a lot of time thinking about and talking about the digital economy, but remind us how much economic activity remains tethered to physical work.

Ani Kelkar (2:32)

I think the thing that people miss is the physical economy is enormous. Forty-four percent of paid work hours globally across sectors are tied to physical work.

The physical world is complex. We move things, we make things, we inspect things, we transport goods, smart set, we operate factories, buildings, vehicles, and infrastructure.

It's a broad set of capabilities that we've deployed for many years and optimized. Roughly 40 percent of working hours are being spent on physical activity and using our McKinsey Global Institute estimates, we think about 13 percent of all of those work hours are automatable today already. This doesn't mean that those jobs are going to go away. In fact, those jobs will likely get reinvented. It's just giving you a scale of how massive the physical economy is, and that's really what makes physical AI interesting.

Lucia Rahilly (3:30)

Yeah, that's amazing.

Mark, let's turn back to you. Give us a sense of the shape this new physical economy will take. In other words, we've said that physical AI is bigger than just robots. What do you expect the form factors and the applications to look like over the next, say, decade or so?

Mark Patel (3:52)

Even within a form factor, we should expect that there will be different applications. I think that's not necessarily how we've experienced, for example, robotics in the past. Robots in the past tended to be defined and implemented for one specific task, but we may have form factors that are actually capable of multiple tasks. A mobile robot could move inventory in a warehouse, but it could also be inspecting that same location for the purposes of safety security. You can have a building system that is designed to automate, for example, the heating and ventilation, but is also controlling lighting in the building.

The use cases that actually will come relatively quickly, things like in the context of moving things around in a commercial context, forks, lifts, tractors, industrial inspection equipment, robot arms that are enabled for security and safety purposes. These may not be visible to most of us, but they're going to be addressing some of those categories of productivity that Ani referred to which are the base load of a lot of the economic impact. In the near term, this is likely to be a lot about mobility, and a lot about specialized equipment, because that's where the technology maturity and the commercial use case intersect, and you've got a near term opportunity.