The cost of physical AI robots varies significantly, with estimates ranging from $2 to over $35 per hour, according to a Roland Berger study and reports cited by fortune.com. This disparity highlights a key issue in the robotics industry: the amount of productive work a robot can reliably perform in real-world conditions. The economics of robot deployment depend heavily on utilization rates, which affect whether robots become cost-effective labor alternatives.
Calculating a robot’s hourly cost involves dividing its purchase or lease price by the productive hours worked over its lifespan, plus expenses like power, maintenance, software, integration, and supervision. The Roland Berger study’s $2 per hour figure covers running costs such as energy and software but excludes the purchase or lease price. This figure assumes robots operate at 60-70% utilization, which is necessary to compete with average U.S. warehouse human wages, according to fortune.com.
The wide range in cost estimates—from $2 to more than $35 per hour—reflects differences in deployment conditions and robot productivity. For example, a $90,000 industrial robot amortized over five years requires high utilization to reach lower hourly costs. This variability influences whether physical AI robots remain pilot projects or scale into a labor market worth trillions of dollars. The industry’s future depends on improving robot reliability and productive time in complex environments.
The analysis underscores that robot cost-effectiveness is not solely about price but about maximizing productive hours. The next major milestone for the sector will be achieving consistent high-utilization deployments that can compete with human labor costs, as detailed in the Roland Berger study referenced by fortune.com.