Can AI-driven humanoid industrial robots solve the problem of reshoring in the U.S. manufacturing industry? A 5-10 year outlook analysis

$Tesla(TSLA.US) has had some exchanges with GPT deep research regarding the title question and has engaged in interaction. In fact, this question has considerable long-term significance. For Dongda, the greatest uncertainty regarding whether it can continue to maintain a sustainable advantage in manufacturing in the future comes from two aspects, one of which is: AI-driven humanoid industrial robots.

Can AI-driven humanoid industrial robots solve the problem of reshoring American manufacturing? A 5-10 year outlook analysis

Introduction: With the development of artificial intelligence and robotics technology, the United States hopes to enhance domestic manufacturing competitiveness through "reshoring." However, domestic manufacturing faces persistent issues such as high labor costs, skill shortages, supply chain dependencies, insufficient production flexibility, and aging infrastructure. The emergence of AI-driven humanoid industrial robots (robots with human-like perception, decision-making, and operational capabilities) in recent years has raised high expectations. Can they systematically address the aforementioned challenges in the next 5-10 years? This article will analyze seven aspects: technological maturity, application capabilities, cost structure, impact on manufacturing structure, policy and capital support, social acceptance and ethics, and a comparison of manufacturing between China and the U.S., supplemented by data and charts to assess long-term trends.

1. Technological Maturity: Current Status and Commercialization Process in the Next 5-10 Years

Current Development Level: Humanoid robots have long been a frontier challenge in the field of robotics. Recent breakthroughs in mechanical hardware, motion control, and AI have gradually brought humanoid robots from the laboratory to industrial prototypes. For example, Boston Dynamics' Atlas, Tesla's Optimus, and Agility Robotics' Digit have successively appeared and demonstrated capabilities such as walking and handling. Traditional automakers (like Honda's ASIMO historical project) laid the foundation, and now many technology and startup companies are making significant investments in this field, including Agility Robotics, Apptronik, Figure AI, and Sanctuary AI. In this wave of enthusiasm around 2023, a large amount of venture capital has poured in: for instance, Figure AI is valued at $2.6 billion, Agility Robotics at $1.2 billion, and tech giants like Microsoft, OpenAI, and NVIDIA are also participating in investments. It can be said that the "dual drive" of technology and capital is accelerating the development of humanoid robots.

Current Technological Bottlenecks: Although it is now possible to achieve bipedal walking, object handling, and a certain degree of human-robot interaction, existing humanoid robots still fall short of being truly capable of complex industrial tasks. For example, some prototypes have limited degrees of freedom (DoF), with only about 20 joint degrees of freedom, making it difficult to perform delicate assembly operations that require human dexterity Stable and reliable autonomous decision-making is still in the early stages, and fully autonomous operation in complex environments requires multiple iterations of algorithms and hardware. "Being able to run and jump" does not equal "being able to work." Currently, many dazzling demonstrations (such as dancing and backflips) are pre-arranged and have not yet reached the level of flexibly responding to various changes on the production line. This means that the technological turning point has not truly arrived.

Progress expectations in the next 5-10 years: Experts predict that the next 5-10 years will be a critical period. Goldman Sachs analysis suggests that humanoid robots will struggle to achieve the efficiency of human workers in the next 2-3 years, but meaningful applications are expected to emerge in 5-10 years. They anticipate that by 2027, global shipments of humanoid robots could reach 76,000 units, increasing to 502,000 units by 2032. Morgan Stanley points out that achieving large-scale commercial use still requires continuous improvements in algorithms and hardware, but also observes that the Chinese industry is accelerating (many Chinese manufacturers plan to mass-produce hundreds or thousands of robots around 2025). On the other hand, optimists like Jensen Huang, CEO of NVIDIA, have stated that breakthroughs in humanoid robots will occur "within five years" (based on confidence in AI and robotics), and Gartner predicts that by 2027, 10% of newly sold logistics robots will be humanoid. Overall, the next decade is seen as a ramp-up period for humanoid robots to transition from prototypes to commercialization: small-scale deployment around 2025, moving towards large-scale applications around 2030. During this process, unit costs, reliability, and safety are expected to improve significantly, laying the foundation for broader implementation.

2. Application Capability: Operability and Efficiency in Industrial Scenarios

Current application scenario examples: Although humanoid robots have not yet become widespread, they have begun to test typical industrial tasks. For example, in the automotive manufacturing sector, China's UBTech has announced that it will deploy its humanoid robot Walker S at Dongfeng Liuzhou Motor's factory to inspect seat belts, door locks, and lamp covers, perform fluid filling, front axle assembly, and material handling tasks to replace repetitive labor on the assembly line. These robots can also collaborate with traditional fixed automation equipment to achieve flexible unmanned production in complex scenarios and undertake more challenging tasks such as quality inspection and in-plant logistics. In the United States, Tesla has deployed multiple Optimus prototypes at its California factory for simple processes such as material handling. Logistics and warehousing is another hot area—e-commerce giant Amazon is testing Agility Robotics' bipedal robot Digit to complete the integration and handling of cargo boxes (material boxes) within warehouses. Digit can autonomously perceive, grasp, and move heavy storage boxes (weighing up to 16 kilograms) in aisles originally designed for humans, placing boxes onto conveyor belts. These early cases indicate that humanoid robots are already capable of handling specific repetitive tasks such as material handling, tightening simple components, and inspection, especially in positions wherelabor is scarce or safety risks are high.** Figure 1: The Digit humanoid robot developed by Agility Robotics collaborates with employees to move boxes in an Amazon warehouse (scene from an experimental warehouse in Washington State, USA). These bipedal robots can autonomously perceive and grasp boxes, walk in human environments, and perform storage container organization and transportation tasks that were previously done by humans. Introducing humanoid robots in the warehousing sector, which faces labor shortages, can reduce manual physical labor and achieve higher automation.

Can they replace humans: Efficiency and flexibility comparison: For simple, repetitive, and non-dangerous tasks, humanoid robots have shown potential for replacement: they are tireless, operate 24 hours a day, and have stable precision and high consistency. For example, in the welding field, traditional industrial robots have achieved millisecond-level precise welding, avoiding errors that may arise from human operation; humanoid robots equipped with welding tools can also perform welding or polishing processes at different locations. However, in many complex assembly and high-precision tasks, current robots still cannot match skilled workers. For instance, tasks such as assembly of tiny parts, wiring, and quality inspection require high dexterity and instant judgment, which robots currently struggle to perform. In terms of work efficiency, a Goldman Sachs survey indicates that the current work efficiency of humanoid robots is unlikely to catch up with humans in the next 2-3 years, and many movements are still not agile or smooth enough. In practical tests, Digit's speed in warehouse handling is only at a preliminary level compared to humans. However, robots have great potential for continuous improvement: with the emergence of stronger AI and more dexterous end-effectors, their operating speed and precision are expected to gradually improve. In multi-variety small-batch production environments, humanoid robots have unique advantages over traditional rigid automation: their human-like shape allows them to work in existing manual production lines and tooling environments, without the need to completely redesign the production line. This means that when product design changes or production processes are adjusted, reprogramming or training the robots can enable adaptation, offering flexibility far beyond dedicated equipment. Therefore, in the short to medium term, humanoid robots are more likely to be "a supplement to human labor" and "an extension of existing automation"—first filling labor gaps and performing heavy and dangerous jobs, collaborating with workers rather than fully replacing them. Industry experts also believe that in the foreseeable future, humanoid robots will play a niche role in factories and will not quickly replace existing collaborative robots, six-axis robotic arms, and other automation equipment. Overall, within the next 5-10 years, humanoid robots will gradually expand the range of industrial tasks they can perform: starting with handling, loading and unloading machine tools, and quality inspection in "dirty, heavy, and dangerous" processes, and gradually expanding to medium-complexity assembly, achieving human-robot collaborative production lines. Fully replacing skilled workers for complex assembly will still require a longer period of technological accumulation.

3. Cost structure: Trends in procurement, usage, and maintenance costs

Trends in hardware procurement costs: Historically, humanoid robots have been extremely expensive R&D projects, but costs are rapidly decreasing with technological advancements and large-scale manufacturing In the past decade, the performance of key components such as drive motors, reducers, sensors, and batteries has improved while prices have decreased. For example, the rise of mobile robots (AMR) has significantly driven down the prices of actuators and sensors, reducing the cost of building humanoid robots by about 90% compared to the past. According to industrial media reports, the material and assembly cost of manufacturing a humanoid robot is currently around $100,000, whereas it could have been as high as a million dollars in the past. This reduction is remarkable. Chinese manufacturers have more aggressive cost control due to localized supply chains: the industrial version of the humanoid robot from UBTECH currently costs as low as $40,000 to $50,000. Tesla has projected that the target price for its Optimus robot after mass production will be $20,000 to $30,000. Additionally, the startup Unitree has launched a low-cost small humanoid robot, priced at only $16,000 (with basic functions). It is evident that in the coming years, the prices of advanced models are expected to gradually approach the price range of mid-range cars, while low-end simplified models may be comparable to the prices of high-end industrial robotic arms. This indicates that the barrier to purchasing humanoid robots is decreasing. If we follow UBTECH's predictions, as costs further decrease with economies of scale, the economic feasibility of robots replacing human labor will improve.

Usage and Maintenance Costs: In addition to the one-time purchase cost, companies will also consider the usage costs over the robot's entire lifecycle, including energy consumption, daily operations, and maintenance. In terms of energy, humanoid robots are mostly electrically powered, and the cost of charging electricity is relatively negligible compared to labor wages. For example, even if a robot works continuously for a whole day, its electricity cost may only be a few dollars, compared to the hundreds of dollars in daily wages for human workers, which is an order of magnitude difference. Regarding maintenance, currently, high-end robots require specialized personnel for maintenance, which can be costly, but as designs mature and reliability improves, the unit maintenance cost will decrease. Furthermore, the emerging Robots as a Service (RaaS) business model packages usage and maintenance costs into a "per hour rental price," reducing the initial investment pressure on users. For instance, the CEO of Agility Robotics revealed that they offer the Digit robot (including supporting accessories and maintenance) to customers at about $30 per hour, allowing customers to replace the all-inclusive cost of about $30/hour for human labor, which can recover the investment within two years. Converting this, a robot working around 2,000 hours a year costs about $62,400, comparable to the annual salary of a U.S. manufacturing worker, but robots can operate continuously in multiple shifts, effectively replacing the workload of about 2-3 human workers within two years. This confirms that its ROI (Return on Investment) has entered an acceptable range. As reliability improves, the average time between failures for robots will extend, and maintenance frequency will decrease, further lowering the depreciation cost of maintenance per working hour. Some analyses suggest that in the future, the marginal cost of robotic labor will approach zero, and with large-scale deployment, the usage cost will mainly consist of electricity and minimal maintenance Of course, the current stage of robot deployment still requires significant upfront investment, but the overall cost curve is rapidly declining. Goldman Sachs reports that the cost of humanoid robots has decreased by 40% over the past year, and this trend will continue, driving the market size to reach $38 billion by 2035. Therefore, in the next 5-10 years, humanoid robots will become increasingly economically attractive: the costs of purchase/rental are continuously decreasing, combined with year-round high utilization rates, the unit labor cost is expected to be lower than that of human labor and continue to decline. It is foreseeable that in high-wage countries (such as the United States), the early adoption of humanoid robots will bring significant cost advantages, further stimulating more companies to invest in this technology, thus forming a cost-application positive feedback loop.

4. Impact on Manufacturing Structure: Ecological Reconstruction, Talent Bottleneck Relief, and Flexibility Improvement

Labor Structure and Talent Bottleneck: The U.S. manufacturing industry has long faced a shortage of skilled workers, with many young laborers unwilling to engage in repetitive production line work. The introduction of humanoid robots is expected to significantly alleviate this talent bottleneck. First, it reduces the demand for a large number of frontline workers. Robots can take over tedious, heavy, and dangerous positions, allowing human labor to shift to supervisory control, equipment maintenance, and other roles. As a result, manufacturing companies will become less dependent on the number of workers, and the labor shortage issue will be alleviated. Meanwhile, the talent demand in manufacturing will shift from low-skilled, repetitive labor to high-skilled, technical support. This requires the industry to retrain the existing workforce to enable them to take on new roles such as robot operation and programming maintenance, thus achieving a "new type of workforce composed of machines and humans." Governments and enterprises need to collaborate to provide skills training programs to cultivate traditional manufacturing workers into robot technicians, avoiding the emergence of new skill gaps. Ideally, robots fill job vacancies while humans gain skill upgrades, leading to a qualitative improvement in the talent dilemma of U.S. manufacturing. Of course, in the short term, the transformation process will also be accompanied by growing pains: some positions will be replaced, and some workers will need to transition or face the risk of unemployment (see the social impact section later). Overall, the application of humanoid robots provides a technical path to solve the labor bottleneck in manufacturing, but it requires policy support for training to transform it into an opportunity for optimizing the talent structure.

Productivity and Scalability: The large-scale adoption of robots will bring productivity improvements and economies of scale. Robots can operate year-round at a stable speed, reducing losses caused by human downtime, fatigue, and errors. This will increase the output per production line and reduce the defect rate. Economic research shows that industrial robots can improve factory efficiency and output, even though they simultaneously replace some positions. For the United States, introducing more robots will help reverse the manufacturing cost disadvantage caused by high labor costs in the past. Automation is seen as the key to improving productivity and bringing manufacturing back to the U.S. When labor costs are no longer a major burden, U.S. factories can approach or even be lower than overseas production costs Companies can also expand their production capacity more boldly, as increasing capacity mainly involves investing in additional robots rather than proportionally increasing staff, making scaling easier. Furthermore, robots enable the possibility of "lighthouse factories" (highly digitalized and automated factories), and in the future, there may be "unmanned factories" operating multiple shifts to maximize capacity utilization. In the long run, the improvement in automation levels will significantly enhance the scalability of American manufacturing, supporting its participation in the global market with high efficiency and low cost.

Flexible customization and decentralized manufacturing: Traditionally, the model of large-scale production in low-cost countries like China, with design and services from the U.S., has led to insufficient flexibility and supply chain dependence in American manufacturing. Humanoid robots have the potential to change this ecosystem. Due to their versatility and reprogrammability, American companies can establish highly flexible manufacturing units domestically: the same batch of robots can switch to produce different products based on order needs, allowing for parallel large-scale and customized production. For example, a production line equipped with robots and a few engineers can produce automotive parts this week and adjust to produce medical devices next week, without needing to relocate production to different countries or undergo lengthy line modifications as in the past. This will shorten the supply chain, bring it closer to the end consumer market, and improve responsiveness to demand changes. Furthermore, as robots reduce the need for labor concentration, manufacturing activities can be more decentralized. Small "micro-factories" can be established across the U.S. and near customer regions, with robots performing the main assembly and one or two engineers monitoring. Such a distributed manufacturing network enhances supply chain resilience: even if one node is obstructed (such as by a pandemic or disaster), other nodes can quickly ramp up output to fill the gap. In summary, driven by humanoid robots, American manufacturing may shift from the past centralized and rigid model to a decentralized and flexible new paradigm. The U.S. is expected to rebuild its domestic supply chain system, achieving self-sufficiency or near-shore production in key areas, reducing dependence on overseas (especially East Asia) sources. This has significant implications for national strategic security and supply chain independence.

Reconstruction of the manufacturing ecosystem: If humanoid robots are widely adopted, the ecological landscape of American manufacturing will also be reshaped. On one hand, traditional labor-intensive industries (such as clothing and simple assembly) that have almost entirely moved abroad due to cost reasons will have the opportunity to re-establish roots in the U.S., using robots to replace cheap labor for production. On the other hand, a domestic robotics industry chain will also emerge, including the manufacturing of robotic bodies, core components (such as high-precision reducers, servo motors, sensors), and system integration, forming new industrial clusters. Leading companies in various industries may invest in developing customized intelligent robot solutions, and the integration of manufacturing and high technology will reach unprecedented levels. At the same time, we will see changes in the employment structure of manufacturing: the proportion of basic assembly workers will decline, while new professions such as software and hardware engineers, maintenance technicians will emerge, raising the average skill level of manufacturing workers This is expected to improve the manufacturing industry's "labor shortage" and social image, attracting more technically educated young people to join, forming a positive cycle. Of course, the entire ecological reconstruction is not achieved overnight; companies need to overcome various challenges during the transition period (technical adaptation, capital investment, employee placement, etc.). However, judging from the long-term trend, humanoid robots will become a key pillar in revitalizing American manufacturing, endowing it with the previously missing cost advantages and flexible responsiveness, thereby winning a more proactive position in the global value chain.

5. Policy and Capital: The Support and Investment Trends in the U.S.

Policy Support: Federal and Local Initiatives – The U.S. government has recognized the strategic significance of robots and AI for future manufacturing competitiveness. In recent years, several supportive trends have emerged at the policy level:

• R&D Funding and Strategic Planning: As early as 2011, the U.S. launched the National Robotics Initiative (NRI), which has been upgraded multiple times (currently NRI 3.0) to fund innovations in basic research and applications of robotics in academia and industry. The CHIPS and Science Act, passed in 2022, also prioritizes advanced manufacturing technologies, including investments in robotics and automation-related R&D. The think tank Special Competitive Studies Project (SCSP) has further suggested that the government formulate a National Robotics Strategy to accelerate domestic production of robots and key components through financial incentives such as tax credits, subsidies, and loans. They point out that deploying robots is a way for the U.S. to overcome labor shortages and enhance competitiveness. The White House also emphasized in the National Advanced Manufacturing Strategy released in 2023 the need to accelerate the deployment of AI and robotic technologies across various industries in the U.S. to maintain manufacturing leadership.

• Incentives for Manufacturing Reshoring: In recent years, federal and state governments have introduced several measures to encourage companies to invest in manufacturing in the U.S., including incentives for automation equipment investment. For example, the accelerated depreciation tax policy allows companies to enjoy income tax reductions when purchasing robots and other capital equipment, thereby reducing the actual costs of automation transformation. Some states (such as Michigan and Ohio, which are manufacturing hubs) provide special subsidies to support small and medium-sized manufacturers in purchasing robots to achieve smart manufacturing upgrades. At the same time, projects like the American Manufacturing Expansion Program provide loan guarantees and land incentives for manufacturing facilities adopting advanced technologies. These policy signals convey a clear message: the government encourages the use of robots to enhance domestic manufacturing competitiveness.

• Industry Alliances and Military Funding: The Pentagon has formed the Advanced Robotics Manufacturing Institute (ARM Institute) with industry to promote the application of robotic technology in defense and commercial manufacturing through public-private partnerships. The government also supports the establishment of robot safety standards and certifications to clear regulatory obstacles for the deployment of new humanoid robots. Overall, while the U.S. does not directly provide "large subsidies" for purchasing robots like some countries, it creates an environment conducive to the development of the robotics industry through various means such as taxes, R&D funding, and public procurement Capital Investment: The Private Sector Leads Innovation – Echoing the orderly support from the government, private capital shows great enthusiasm in the field of humanoid robots:

• Tech Giants' Self-Research and Layout: Major tech and manufacturing companies such as Tesla, Boston Dynamics (acquired by SoftBank and Hyundai), Amazon, and Google are investing heavily in the research and development of general-purpose robots. Tesla is not only developing the Optimus robot but is also investing in the supply chain to try to control the manufacturing of core components. Amazon is accelerating the use of robots in logistics through acquisitions and strategic investments (such as acquiring Kiva Systems for warehouse robots and investing in Agility Robotics). Google's parent company Alphabet has established subsidiaries like Intrinsic to focus on industrial robot intelligence. The entry of large enterprises brings both capital and application scenarios, helping humanoid robots move from the laboratory to the factory.

• Active Venture Capital: In the startup sector, dozens of humanoid robot startups have emerged in the past two years, attracting the attention of top venture capital. Statistics show that there were over a hundred robot startup financing events globally from 2022 to 2023, with several single financing rounds exceeding $100 million. American companies like Figure AI raised over $100 million in one go, Agility Robotics secured over $180 million in multiple financing rounds, and Sanctuary AI also received strategic investments including from Microsoft. Venture capitalists are attracted to the enormous potential market for humanoid robots: applicable in manufacturing, logistics, healthcare, services, and other trillion-dollar industries. Reports predict that the humanoid robot market could reach hundreds of billions of dollars by 2035, and the capital market is unwilling to miss the next "smartphone-level" explosive opportunity.

• Capital Drives Mergers and Collaborations: The influx of capital has also driven cooperation and integration within the industry. For example, automotive parts giant Magna has invested in multiple robot projects to seek synergies; after acquiring Boston Dynamics, Hyundai Motor Group further invested resources to accelerate its commercial pace. Traditional industrial robot companies (ABB, Fanuc, etc.) have also begun to layout humanoid robots through investments in startups or internal incubation to avoid missing the next wave of technological advancement. The catalytic effect of capital has led to shortened R&D cycles and accelerated product iterations. It is foreseeable that in the coming years, there will be more IPOs and mergers and acquisitions in this field, gradually clarifying the industrial landscape.

In summary, under the joint action of the policy “visible hand” and the capital “invisible hand”, the U.S. humanoid robot industry has entered a fast track of development: the government provides directional guidance and basic support, while market funds accelerate the productization of technology and commercial implementation. This synergy between government and enterprises is expected to compensate for the U.S.'s lag in manufacturing automation, helping American manufacturers adopt this emerging technology more quickly, thereby serving the overall trend of manufacturing return.

6. Social Acceptance and Ethical Risks: The Impact of Labor Replacement and Responses Impact on Employment and Public Attitudes: The large-scale application of industrial robots inevitably raises concerns about employment and social impact. Polls show that the majority of Americans are worried about machines replacing human labor. A survey by the Pew Research Center indicates that only 33% of respondents have a positive view of machines widely taking on human jobs, while as many as 72% are concerned about this prospect. The public is particularly worried about increased inequality: 76% of Americans expect that if machines can perform a large number of human jobs, the gap between the rich and the poor will widen further. They generally doubt whether the economy can create enough new jobs to compensate for those eliminated (only 25% believe that many higher-paying new jobs are likely to emerge). These data reflect that a significant portion of society is concerned about potentially becoming victims of the automation wave.

However, there are also positive factors that encourage society to gradually accept robots in the workplace. First, there is currently a real issue of difficulty in hiring and high labor costs in the manufacturing sector, and both businesses and the public realize that “no one is available” is more realistic than “being replaced by robots.” In some positions (such as assembly line work and warehouse handling), robots are seen as a necessary means to alleviate labor shortages, and this awareness has deepened in recent years due to the pandemic and supply chain disruptions. Assembly magazine points out that society's acceptance of robots is rising, and under the pressure of labor shortages and efficiency demands, the current timing is favorable for introducing humanoid robots into commercial environments. Secondly, the public supports robots taking on dangerous and dirty jobs. Most people agree to let robots do the work that humans are unwilling to do or that poses safety risks, freeing humans to engage in safer and more creative tasks. This provides social permission for the application of robots in high-risk fields such as mining, welding, and chemicals.

Labor Transition and Policy Response: Although technological progress often creates new job opportunities in the long run, the unemployment and job transition impacts during the transition period cannot be ignored. Therefore, it is necessary for the government, businesses, and the education system to work together to mitigate the impact of automation on the workforce. Several policy ideas are currently being discussed:

• Retraining and Education: This is the most direct and important measure. The government can allocate funds to collaborate with businesses to establish vocational training programs, training affected industrial workers as robot operators, maintenance technicians, and other new positions. For example, after a factory introduces robots, original assembly workers can undergo a few months of training to become production line technicians, shifting from “hands-on work” to “monitoring and debugging.” This job transition training can maximize the value of the existing workforce, ensuring that automation and employment do not become a zero-sum game.

• Social Security and Compensation: For those who truly cannot transition or are unemployed in the short term, a comprehensive social security system is essential. Some policy suggestions include temporary unemployment benefits, robot tax (taxing companies that benefit from using robots to subsidize unemployed workers), and even public calls for Universal Basic Income (UBI) as a safety net in the age of automation Although UBI is politically controversial, similar ideas have entered policy discussions.

• Employment Restrictions and Transition Arrangements: Certain industry unions may seek agreements to ensure a certain percentage of human jobs or set transition periods when introducing robots. For example, the United Auto Workers (UAW) recently focused on the impact of electrification and automation on employment during labor negotiations, hoping companies would provide priority for new positions and salary guarantees. Policymakers could also consider incentivizing companies to adopt a "human-machine collaboration" model rather than a "one-size-fits-all replacement," such as offering tax breaks to companies that hire workers displaced by robots to encourage internal absorption of redundant personnel.

Ethics and Safety: Beyond employment, the ethical issues brought by humanoid robots also include: workplace safety (is it safe for humans and robots to coexist, how to prevent robot-related injuries), algorithmic bias (will robot decisions disadvantage certain individuals), dignity of personnel (the psychological impact of working alongside robots), etc. Fortunately, industrial robots already have mature safety standards (such as ISO 10218) and practical experience, and collaborative robots (cobots) have rarely had accidents while working alongside humans in factories in recent years. This is thanks to safety designs such as speed and force limits, and collision detection. Humanoid robots will also adopt similar or even more advanced sensing and speed-limiting mechanisms to ensure personal safety. Additionally, robot management requires data ethics to ensure that collected visual and audio data is not misused. Overall, technical specifications and legal regulations need to keep pace with the times, defining behavioral boundaries for the new generation of autonomous robots.

Long-term Outlook on Social Mindset: Historical industrial revolutions indicate that as technology becomes widespread, society will gradually adjust its perceptions. Initial anxieties about machines replacing jobs may ease with the emergence of new industries and positions. If the benefits brought by humanoid robots (more output, cheaper local products, reduced burdens on workers, etc.) are widely perceived, social acceptance will increase. Particularly, the younger generation is more adaptable to technology, and the future workforce may view robots as everyday tools and colleagues. In an ideal scenario, collaboration between humans and intelligent machines will become the norm, with society avoiding polarization through education and policy innovation, achieving labor transformation and upgrading. To reach this point, preparations need to start now: not only technically enabling robots to work "like humans," but also ensuring that the institutional environment guarantees that people can work, learn, and live with dignity.

7. Comparison of Manufacturing Competition Patterns between China and the U.S.: Prospects for Cooperation and Competition under the Popularization of Humanoid Robots

The Rise of Automation in Chinese Manufacturing: Discussing the impact of humanoid robots on the competitiveness of U.S. manufacturing cannot be separated from comparisons with China. While the U.S. hopes that robots will help "bring manufacturing back," China is also mobilizing national efforts to promote automation and upgrading in manufacturing. In fact, China has become the fastest-growing market for industrial robot applications globally. According to the International Federation of Robotics (IFR), in 2023, the robot density in China's manufacturing sector (the number of robots per 10,000 employees) has reached 470 units, ranking third in the world, behind South Korea and Singapore, and surpassing the U.S. figure of 295 units. China has more than doubled its robot density in just a few years, while the United States currently ranks tenth in this metric (see the chart below):

Figure 2: Comparison of Industrial Robot Density in Manufacturing Industries by Country in 2023 (Number of Robots per 10,000 Employees). It can be seen that China's robot density is 470 units, significantly surpassing the United States' 295 units. This reflects China's massive investment and rapid deployment in industrial automation in recent years. South Korea and Singapore still occupy the top positions, but China has already overtaken traditional manufacturing powerhouses Germany and Japan, and is closing in on the leading group. In contrast, the automation level of U.S. manufacturing has increased relatively slowly. To narrow this gap, the U.S. needs to accelerate the adoption of advanced automation technologies, including humanoid robots, in the future.

China is also moving quickly in the field of humanoid robots. In terms of policy, the "Made in China 2025" plan has long listed high-end robots as a key development direction. In early 2023, 17 government departments in China jointly released an action plan to promote the development of the robot industry, clearly supporting humanoid robots and other cutting-edge directions【32†】. Local governments are also competing to introduce subsidies and industrial parks to attract robot projects. In terms of the supply chain, a complete set of local component suppliers has emerged in China, such as gearbox manufacturers and servo motor manufacturers, along with the boost from the consumer robot (vacuum cleaners, drones) industry, making the procurement of parts needed for humanoid robots more convenient and cost-effective. Research by Morgan Stanley indicates that Chinese humanoid robot startups account for a significant proportion globally, benefiting from a mature local supply chain, a vast local application market, and government support. In terms of enterprises, there are not only companies like UBTECH, Yunshen (developing the H1 robot), and Unitree focusing on humanoid robots, but also large enterprises like Huawei and Xiaomi that have begun to showcase humanoid robot prototypes. The new automotive force XPeng even showcased a humanoid robot during the 2023 Spring Festival Gala. This situation of widespread public attention and diverse developments suggests that China may achieve large-scale commercial use of humanoid robots the fastest. For example, UBTECH plans to achieve mass production of robots by 2025-2026. According to statistics, the scale of China's humanoid robot industry in 2023 is approximately 3.91 billion yuan, a year-on-year increase of 85.7%, and it is expected to exceed 20 billion yuan by 2026, with an astonishing annual growth rate. It can be said that China is seizing the opportunity of this robotic revolution, hoping to consolidate its position as the "world's factory" and transition to intelligent manufacturing.

Analysis of U.S. Relative Competitiveness: Against this backdrop, even if the U.S. achieves the popularization of humanoid robots domestically, it does not necessarily mean it can "regain" the crown of manufacturing; rather, it is more likely to present a new pattern of the U.S. and China competing to enhance automation levels and reshape manufacturing advantages:

• Convergence of Labor Cost Differences: In the past, a significant advantage of Chinese manufacturing over the U.S. was low wages, but as labor costs in China rise and the U.S. introduces robots to reduce labor expenses, the gap in unit manufacturing costs will narrow. When factories in both countries are primarily operated by robots, labor costs will no longer dominate, and competition will shift more towards energy, land, capital, and other factors The United States has certain advantages in energy (the shale gas revolution has brought cheap natural gas and relatively stable electricity prices), as well as cheaper industrial land and advanced management. However, China's infrastructure (electricity, logistics) is also very well-developed, and the government can provide more favorable industrial energy prices. Therefore, in terms of pure production costs, both sides may tend to be evenly matched.

• Supply Chain and Industrial Clusters: The complete industrial chain ecosystem accumulated by China over decades is difficult to shake in a short time. Even if the U.S. produces certain electronic products domestically using robots, it still needs to source components and materials globally, especially from China, making this supply chain dependence hard to completely eliminate in the short term. The benefit of local vertical integration in China is that the necessary supporting manufacturing can be obtained nearby, resulting in high production synergy efficiency. Therefore, the U.S. needs significant investment and time to rebuild its domestic supply chain. Humanoid robots can help the U.S. solve labor issues, but they cannot immediately replicate a Chinese-style industrial ecosystem. However, in some strategic industries (such as semiconductors, pharmaceuticals, and defense products), the U.S. may achieve partial supply chain relocation through robots and policy support, reducing dependence on China. This is more likely to be selective competitiveness reconstruction rather than an overall industry catch-up.

• Technological Innovation and High-end Manufacturing: The U.S. still has advantages in core technological innovation, especially in software, AI algorithms, and high-end equipment. This means that humanoid robots developed in the U.S. may be half a step ahead in intelligent decision-making and software ecosystems, leading to differences in production quality and efficiency. For example, industrial AI systems developed by U.S. companies may allow robots to adapt to new tasks more quickly and optimize production processes collaboratively, thus achieving a win-win in quality and efficiency in high-end manufacturing. If the U.S. can leverage robots to establish a lead in the manufacturing of high value-added, high complexity products (such as aerospace, cutting-edge electronics, and biomedical devices), it can avoid direct cost competition with China in mid- to low-end products, forming a differentiated competitive advantage. Conversely, China is also catching up in high-end manufacturing automation, and the U.S. needs to continue investing in R&D to maintain its technological barriers.

• Policy and Institutional Environment: The market-oriented environment in the U.S. encourages innovation, but sometimes strict labor and environmental regulations and strong labor organization power may slow down the implementation of automation (companies are concerned about social backlash or compliance costs). In contrast, China can relatively concentrate its efforts when promoting robots, facing less resistance to automation in factories (society's concern about unemployment due to automation is relatively lagging behind that of the U.S.). This difference may lead to different speeds of technological diffusion: the U.S. may be more cautious in the early stages, rolling out widely only after sufficient pilot verification; China may rapidly apply from the top down but make remedial optimizations in individual links later. In the long run, both countries have their own trade-offs in efficiency and social costs. If the U.S. can formulate reasonable policies to balance innovation and employment, it may achieve both automation and social stability, thus winning in overall national strength Long-term Trends in Global Manufacturing Patterns: With the maturation of technologies such as humanoid robots, new trends are expected to emerge in the global manufacturing landscape:

• “Robot Dividend” Replacing “Demographic Dividend”: In the past, manufacturing shifted to labor-rich regions, but now robots are prompting a reconsideration of proximity to markets and innovation centers. In the future, production activities may return to the countries where consumer markets are located (such as North America and Europe), as the advantage of cheap labor diminishes, replaced by automation efficiency. This presents opportunities for developed countries like the United States: as long as they seize the wave of robotics, it is entirely possible to restore a certain level of manufacturing self-sufficiency and reduce excessive reliance on overseas production.

• Win-win or Collision between China and the U.S.? With the widespread adoption of humanoid robots, both China and the U.S. will improve production efficiency, and global consumers will benefit from lower-cost products and more stable supply chains. The incremental benefits brought by this technological advancement may form a certain degree of win-win. However, from a competitive perspective, both countries aim to dominate manufacturing, which may lead to more intense competition in high-tech industries and standard-setting, and it is even possible that a “two-camp” situation will emerge in the fields of robotics and AI. Those who can lead in this wave of industrial revolution will occupy the economic high ground by the mid-21st century. Therefore, we will see both China and the U.S. fully deploying robotics technology, investing comprehensively in funding, talent, and policies. This is both a race and a push towards a new era in global manufacturing.

• Impact of Other Emerging Economies: It is worth mentioning that the proliferation of humanoid robots will also affect developing countries that traditionally started with manufacturing. If major economies like the U.S. and China engage in large-scale production with robots, the comparative advantages of some labor-rich but technologically lagging countries (such as those in Southeast Asia and South Asia) will be weakened. Global manufacturing may shift towards a technology monopoly rather than a labor-driven model. If the U.S. seizes this opportunity, it will hold significant influence in the new landscape.

In summary, humanoid robots provide the U.S. manufacturing sector with a valuable opportunity to overtake competitors and regain competitiveness, but this is not a technology exclusive to the U.S. Major manufacturing countries like China are also rapidly catching up. In the future, global manufacturing competition will increasingly hinge on automation and AI capabilities. Whether the U.S. can “regain an advantage” through humanoid robots depends on its pace and breadth of advancement, as well as how it reshapes its industrial ecosystem based on this. Similarly, China, which has already taken a step ahead, will not slow down; the U.S. must strive to catch up and leverage its own innovation and institutional advantages to remain undefeated in the new round of industrial revolution.

8. Long-term Trend Outlook: Conclusions and Future Scenarios

Based on the above analysis, AI-driven humanoid industrial robots are expected to partially solve the core challenges faced by the return of U.S. manufacturing in the next 5 to 10 years, but the process will be gradual and complex:

• High Labor Costs: Trend Assessment: Basically alleviated. As the costs of humanoid robots decrease and their performance improves, they will be able to complete a large number of production tasks at a lower “hourly wage.” Especially in high-wage countries like the U.S., robot substitution can significantly reduce manufacturing costs It is expected that in the next decade, the cost of robot work hours will further fall below the average wage of humans, making "robot labor" a more economical choice. This will weaken the cost disadvantages that have previously hindered the return of manufacturing, giving American goods a price competitiveness.

• Skill Shortage: Trend Judgment: Transforming problems into opportunities. As robots take over simple jobs, the demand for low-skilled workers in manufacturing will decrease, alleviating the "no one to hire" dilemma. At the same time, the demand for high-skilled technicians will rise, forcing an upgrade in education and training. This presents both challenges and opportunities: if the U.S. successfully implements large-scale retraining programs for industrial workers, it will have a new workforce that is technically skilled and capable of mastering intelligent production tools, leading to increased productivity and innovation. Conversely, if the transition is not smooth, structural unemployment and skill mismatches may occur. Therefore, talent policies will determine success or failure in the long term.

• Supply Chain Dependence and Security: Trend Judgment: Gradual restructuring and increased localization. With the help of robots, the U.S. is in a position to relocate some key manufacturing processes back to domestic or nearby allied countries, thereby shortening the supply chain radius and enhancing autonomy and controllability. It is expected to start with strategic industries (such as chips, defense, and healthcare) and gradually expand to consumer goods and other fields. In the long run, U.S. manufacturing will form a "domestic + nearshore" new supply chain network: highly automated domestic factories will handle high-value components, while ordinary parts will still be globally sourced, but from more diverse and secure sources. The supply chain will be more resilient, reducing dependence on any single country. However, completely breaking away from global supply chains is unrealistic; international division of labor will still exist, but the U.S. will capture a larger share of the value chain.

• Production Flexibility and Innovation: Trend Judgment: Significant improvement. Humanoid robots provide American industries with the opportunity to embrace flexible manufacturing. In the medium to long term, U.S. factories will be better at quickly switching product lines and customizing production to meet rapidly changing market demands. This flexibility will become one of the competitive selling points of American manufacturing, conducive to incubating more high-value, personalized products. Combined with AI-driven design optimization and digital management, American companies can build an agile innovation-manufacturing closed loop: achieving faster iterations from R&D to production, realizing the model of "American design + American manufacturing + global sales," leading trends in certain emerging industries.

• Infrastructure and Regional Development: Trend Judgment: Upgrading smart manufacturing infrastructure. To support robot deployment, the U.S. needs to upgrade some industrial infrastructure, such as the power grid, 5G communication coverage in industrial parks, and industrial internet platforms. It is foreseeable that the government will invest in building smart factory demonstration zones, robot testing bases, and other supporting facilities. This will drive the revitalization of manufacturing clusters, especially in cities that were once part of the "rust belt," which are expected to thrive again due to the establishment of new factories. Meanwhile, the development of robot technology may also create entirely new industries and services (such as robot maintenance services and system integration solution companies), further improving the manufacturing ecosystem Conclusion: AI-driven humanoid industrial robots are not a panacea, but they do provide tools for leapfrogging the manufacturing industry. In the next 5 to 10 years, they can partially replace labor, reduce costs, and alleviate labor shortages, while initiating a transformation in manufacturing models, creating more favorable conditions for the return of American manufacturing. However, the resolution of core issues is a system engineering challenge: it requires technological maturity, affordability, and more importantly, the coordination of policies, capital, and society. If the U.S. can accelerate the application of robots while ensuring employment and social stability, it will significantly enhance the competitiveness of the manufacturing sector and regain an important position in the "world factory." Looking further ahead (beyond 2035), as the prevalence of humanoid robots increases, global manufacturing may usher in a human-machine collaboration, intelligence-led new era. At that time, the landscape of American manufacturing may be completely transformed—long-standing issues of labor costs and skill shortages will no longer be constraints, and the U.S. will have the opportunity to compete with any country in production and manufacturing based on technological and innovative advantages. In this process, whether the U.S. can truly and systematically solve the return issue will depend on the speed of technological advancement and the capacity for social and economic adaptation. It is certain that the transformation led by humanoid robots has already begun, and its long-term impact will profoundly change the global industrial landscape. The future of American manufacturing is being rewritten by those shining robots currently undergoing trial operations in the workshops.

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