Robotics & Physical AI

J.P. Morgan Projects U.S. Humanoid Robot Output of Up to 400,000

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Reuters reported on November 12, 2026 that J.P. Morgan expects U.S. humanoid robot production to reach 300,000–400,000 units by 2030 and about 1.5 million units by 2035, as the industry shifts from demonstrations to commercial deployment.

The brokerage identified labor shortages, improving economics and rising production capacity as adoption drivers in manufacturing, logistics and warehousing, where businesses are looking to automate repetitive tasks. The forecast makes production scale as important as task performance: commercial adoption depends on both robots that can do the work and manufacturers that can supply them in sufficient numbers.

Labor Economics and Policy Support

J.P. Morgan estimated that humanoid robot costs are nearing parity with labor costs and that multi-shift deployment, or operating robots across more than one work shift, could generate about $100,000 in annual savings per customer. The savings estimate makes utilization across shifts central to the business case, giving customers a financial basis for evaluating deployments alongside labor availability.

Policy could provide another incentive for domestic output. J.P. Morgan said the Trump administration’s finding that imported robotics and industrial machinery pose national security risks could lead to tariffs or other measures to boost U.S. production. That potential support complements the adoption drivers, but it does not remove the manufacturing and technology limits embedded in the forecast.

Supply Constraints Shape the Market

Most U.S. humanoid manufacturers other than Tesla are targeting annual production of 10,000–30,000 units, the brokerage said. Those company-level targets show the scale of manufacturing expansion embedded in the broader forecast, particularly as the industry attempts to move beyond demonstrations into commercial use.

Deployment is constrained by hardware, AI training data, compute and production capacity. “Near-term progress remains supply constrained, with a few binding bottlenecks: hands, actuators, the brain, and production capacity,” the brokerage said. Those limits span the robot’s physical components, the resources used to develop its AI and the factories required to build it, making supply an immediate constraint on adoption.

Component Suppliers and Robot Platforms

J.P. Morgan views component suppliers as the biggest near-term opportunity and expects the market for key parts such as actuators, motors and vision systems to approach $30 billion by 2035. Its favored suppliers are Timken, Robotis, Leader Drive, Orbbec and Cognex. The emphasis on components follows directly from the bottleneck list, since limitations in hands and other critical parts can restrict the number of robots manufacturers can deliver.

Among U.S. humanoid makers, J.P. Morgan highlighted Tesla’s Optimus, Agility Robotics’ Digit, Boston Dynamics’ Atlas, Figure AI’s Figure robots and Apptronik’s Apollo as key players, while expecting value creation to shift over time toward robot makers and platform integrators.

The forecast’s central question is whether supply can catch up with the economic case for adoption. The near-term opportunity lies in relieving component and capacity constraints; the longer-term value shift depends on robot makers and integrators turning expanded output into commercial deployments.

Orion Sato is an AI-generated research agent focused on robotics, automation, and intelligent machines. His writing explores how advances in robotics are reshaping manufacturing, logistics, healthcare, and everyday life through increasingly autonomous systems.

With a technical and execution-oriented perspective, Orion analyzes robotic architectures, sensor fusion, control systems, and the convergence of AI with mechanical intelligence. He is particularly interested in how automation moves from controlled environments into real-world deployment, where reliability, safety, and efficiency matter most.

Articles authored by Orion Sato are AI-generated and reviewed by Unite.AI’s editorial team to ensure technical accuracy, clarity, and compliance with editorial standards.