Short summary: Inspired Capital believes physical AI represents an enormous opportunity as labor scarcity, supply chain pressures, and advances in robotics hardware and software converge. We see three categories where durable companies will be built: software that supports robotic operations, platforms that help businesses adopt physical AI, and vertically integrated producers built around automation.
Physical AI refers to artificial intelligence that enables machines, including robots, to perceive, reason, and act in the physical world. Its applications extend into the factories, infrastructure, and services that shape everyday life.
There’s no single definition of artificial general intelligence, or AGI, but at Inspired Capital, we believe any real version of it must move beyond our screens and succeed in the physical world too. After all, much of the labor that shapes our world and supports national economies remains a physical endeavor. We believe that the opportunity for new companies to create value in the realm of physical AI is orders of magnitude greater than that in the software universe alone. We also believe that we are witnessing a perfect storm of technological, societal, and economic factors that will result in the next trillion-dollar physical AI company being started now.
As a representative example of labor scarcity, a 2024 study from Deloitte and The Manufacturing Institute estimated that U.S. manufacturing could need as many as 3.8 million new employees between 2024 and 2033, with approximately 1.9 million positions potentially remaining unfilled if workforce gaps are not addressed.
These labor force challenges sit alongside demographic realities such as an aging population and falling fertility rates. For businesses facing persistent staffing constraints, automation is increasingly about maintaining a minimum viable capacity as well as cutting costs.
The past decade has taught many company leaders that supply chain resilience needs to be high on the strategic priority list. Nearshoring and the pursuit of domestic production are important levers companies can pull, and we believe the continued pursuit of these strategies will compound the need for robotic labor augmentation.
Hardware costs have fallen substantially, with lidar offering one example of the shift. In a 2020 presentation, Velodyne described products with average selling prices starting at $100, challenging the perception of lidar as a $75,000 technology. At Tesla’s 2024 “We, Robot” event, Elon Musk projected that its Optimus humanoid robot could eventually sell for 20,000–30,000 at scale, presenting that range as a long-term target.
In our view, a central piece of the puzzle lies on the software side: how quickly can a robot scale to generalized intelligence, or at least develop the ability to perform multiple tasks? The answer to that question has historically been too long for many commercial applications.
Now, with robotic foundation models advancing, there is hope of achieving a level of performance that crosses over into a budget-worthy line item for customers. These models offer a path toward more adaptable robotic capabilities, although challenges around training data, safety, and reliable execution remain.
We see three categories where durable companies will be built.
Robotic products won’t themselves be the application layer, but they will require one. Products that support tasks like teleoperation, telemetry, warehouse management system (WMS) integrations, and fleet management at scale will, in our view, find mass adoption as the physical AI universe scales.
Many service industries will find themselves painfully moving through a process of change management akin to the digital transformations of the 2000s and 2010s, but this time it will be about incorporating the right strategy to augment their labor force with robotic automation.
We believe hardware-agnostic platforms that solve this problem for customers will be in high demand. Our portfolio company BrightAI is doing this work for some of the most labor-intensive industrial service categories, including power, water, HVAC, and pest control.
We believe there will be new companies created in food and beverage, textiles, chemicals, and other categories historically dependent on human labor that will operate with significantly reduced cost structures. These businesses will reimagine industries with automation potential at their core.
The wave we are about to see invites a whole set of questions we don’t know the answers to.
How are these products priced and financed, and how are they managed and serviced at scale? How do human staffing models evolve to accommodate a robotic work schedule that runs 24 hours a day, seven days a week? How does insurance get priced to account for the adjusted risk of human and robotic labor collaborating hand in hand? Do we have sufficient energy supply to meet the impending demand?
In our experience, these second derivative implications are often where the most interesting opportunities lie, and if you’re currently thinking about them, we’d love to speak with you.