Morgan Stanley Research estimated in May 2025 that the humanoid-robot market could exceed $5 trillion by 2050. That is a long-range analyst projection—not current robot sales or a forecast of any company’s revenue. Tesla has a humanoid under development, NVIDIA supplies robotics technology and development tools, and ABB has an industrial-robotics ecosystem connection. Those links make the three companies examples of different kinds of exposure, not assured winners or recommendations.
What does the $5 trillion forecast count?
Morgan Stanley’s estimate covers more than sales of finished humanoid robots. It includes related supply chains and repair, maintenance and support, so it should be read as a broad estimate of economic activity associated with humanoids. It is not a measured market size, and it does not mean that robot makers will earn that amount.
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The forecast sketches a market that develops over decades. Morgan Stanley Research projected nearly 1 billion humanoids in use by 2050, with about 90% serving industrial and commercial purposes. Its country projections were 302.3 million units in China and 77.7 million in the United States by that year. These are projections, not confirmed production or adoption figures.
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How do other market forecasts compare?
Published estimates vary widely because they were made at different times, use different horizons and describe different scenarios. Goldman Sachs Research’s 2024 summary described a much smaller baseline estimate alongside a conditional, higher-end scenario; neither should be treated as a direct validation of Morgan Stanley’s 2050 projection.
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| Research estimate | What it says | How to interpret it |
|---|---|---|
| Morgan Stanley Research, May 2025 | More than $5 trillion by 2050 | Analyst projection that includes related supply chains and repair, maintenance and support—not just robot sales. |
| Goldman Sachs Research, summary published February 2024 | At least $6 billion in 10–15 years | Estimate summarized by Goldman Sachs; its date and horizon differ from Morgan Stanley’s. |
| Goldman Sachs Research, summary published February 2024 | Up to $154 billion by 2035 | A blue-sky scenario conditional on progress in design, use cases, technology and affordability, as well as public acceptance—not the base case. |
Morgan Stanley’s separate labor projections illustrate the scale of the adoption assumptions behind its outlook. In 2024, the firm projected 8 million working humanoids in the United States by 2040 and 63 million by 2050. It estimated associated wage impacts of $357 billion by 2040 and approximately $3 trillion by 2050. Those figures are forecasts, not realized employment or wage changes.
Three public companies with different kinds of exposure
The word “positioned” can mean several things: developing a robot, supplying tools used to build robots, or participating in an established industrial-robotics ecosystem. The evidence available for these examples establishes different types of connection; it does not quantify humanoid-related revenue for any of them.
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| Company | Type of exposure | What the cited material establishes | Humanoid revenue evidence |
|---|---|---|---|
| Tesla | Direct developer | Tesla’s 2025 SEC-filed proxy material describes Optimus as under development and states a long-term vision for commercial and home use. | Not stated in the cited material. |
| NVIDIA | Enabling compute, software and development platform | Company announcements describe robotics foundation models, simulation and synthetic-data tools, and a research reference robot assembled with partner hardware. | Not stated in the cited material. |
| ABB | Industrial-robotics ecosystem | NVIDIA’s March 2026 announcement names ABB Robotics among industrial and robotics organizations building on NVIDIA physical-AI technology. | Not stated in the cited material. |
Tesla: the direct-development case
Tesla’s proxy material says it is developing Optimus and presents a long-term ambition to transform labor and productivity in commercial settings and homes. That is evidence of the company’s stated plans, not proof of mass production, completed sales or a meaningful contribution to earnings. A direct-development thesis depends on whether the company can turn its stated ambition into a capable, affordable product and deploy it at scale.
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NVIDIA announced its Isaac GR00T N1 robotics foundation model and supporting simulation and synthetic-data tools in March 2025. In June 2026, it described a GR00T research reference robot pairing a Unitree H2 chassis, Sharpa hands, Jetson Thor compute and NVIDIA software. NVIDIA said Unitree would make the reference robot available in late 2026 and that the workflow would support the Unitree G1. These announcements show development activity and a platform role; they do not establish widespread deployment or consumer availability.
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The distinction matters to an investment thesis: a company can enable robot development without selling the finished robot, and the existence of a platform does not by itself establish how much revenue humanoids generate for its supplier.
ABB: the established industrial-robotics case
NVIDIA’s March 2026 announcement places ABB Robotics among industrial and robotics organizations building on NVIDIA physical-AI technology. That supports describing ABB as part of an industrial-robotics ecosystem connected to the platform. It does not establish that ABB is developing a humanoid product, or reveal the scale or financial materiality of this connection.
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Where else could value accrue?
The humanoid supply chain is broader than the companies that assemble finished robots. Morgan Stanley’s coverage identifies potential exposure across AI and semiconductors, sensors, batteries, actuators, bearings, reducers and systems integrators. Software, simulation and onboard compute are also part of the development stack reflected in NVIDIA’s announcements.
This broader map can help explain why a company may have a thematic connection without being a humanoid manufacturer. But identifying a component category is not enough to establish that a particular public company has a meaningful humanoid business: that requires company-specific evidence about products, customers and financial contribution.
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What could slow adoption?
The market projections depend on technical progress and real-world adoption, neither of which is guaranteed. Morgan Stanley’s research points to continued work in both hardware and AI. The economics also matter: its 2025 estimates put humanoid costs in high-income countries at about $200,000 in 2024, with projected costs of $150,000 by 2028 and $50,000 by 2050. For lower-income countries, it projected a possible $15,000 price by 2050. The later figures are projections, not current quoted prices.
Lower costs alone would not settle whether homes, factories or businesses adopt humanoids. Useful tasks, performance, manufacturing scale, safety, regulation and public acceptance all affect whether projected demand appears. Morgan Stanley’s outlook anticipated relatively slow adoption until the mid-2030s, followed by faster growth in the late 2030s and 2040s; that timing is the firm’s forecast, not a known schedule.
What the forecasts do—and do not—say about stocks
A large projected market is not a stock-return forecast. The cited material does not provide current valuations, a financial screening of these three companies, confirmed humanoid unit sales or quantified humanoid-related revenue. Tesla’s stated development plan, NVIDIA’s platform announcements and ABB’s ecosystem connection are not interchangeable evidence of commercial success.
To assess any company’s exposure, distinguish announcements and ambitions from deployed products and recurring sales. Then ask whether humanoids are financially material to the business, what execution and adoption hurdles remain, and whether the share price already reflects expectations. Without those company-specific and valuation facts, the three examples are best understood as a direct developer, an enabling platform and an industrial ecosystem participant—not as a ranking of likely stock winners.
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