In the heart of Houston, Texas, a revolution is quietly unfolding on the factory floor. Foxconn, the Taiwanese manufacturing giant best known for assembling iPhones, is set to deploy advanced humanoid robots in its new AI server production plant. This move, announced in late October 2025, marks one of the first large-scale integrations of humanoid robotics into industrial manufacturing lines, potentially reshaping how goods are produced worldwide.

The robots, powered by Nvidia’s Isaac GR00T model, are designed to handle complex tasks alongside human workers. According to The Register, Foxconn’s facility will be ‘among the first to deploy humanoid robots powered by the NVIDIA Isaac GR00T N model on its production lines.’ This development comes amid a broader push by tech companies to address labor shortages and boost efficiency in manufacturing.

Pioneering Integration in AI Server Production

Foxconn’s Houston plant is specifically geared toward producing AI servers for Nvidia, highlighting the symbiotic relationship between robotics and AI hardware. The company made a passing reference to this in a recent earnings call, signaling that humanoid robots could soon handle repetitive and precise assembly tasks. ASSEMBLY reports that the factory will be among the first to integrate these robots, with deployment expected in early 2026.

Beyond Foxconn, other manufacturers are exploring similar paths. In Shanghai, China, humanoid robots equipped with embodied intelligence reinforcement learning technology have already debuted on production lines. As detailed by CGTN, these robots represent the world’s first application of such technology in daily industrial scenarios, performing tasks like sorting and assembly with minimal human intervention.

Global Race for Humanoid Deployment

The momentum isn’t limited to Asia. Tesla, under Elon Musk, is advancing its Optimus humanoid robot toward mass production. The Jerusalem Post notes that a large order of linear actuators from China indicates Optimus V3 is nearly complete, with preparations for scaled manufacturing underway. Tesla aims to integrate these robots into its own factories, potentially automating vehicle assembly lines.

Chinese EV maker Xpeng is also accelerating its humanoid ambitions. According to CNBC, Xpeng plans to mass-produce its IRON model by the end of 2026, equipped with solid-state batteries and self-developed AI chips. This follows Tesla’s playbook, blending automotive expertise with robotics to create versatile factory workers.

Technological Foundations Driving Adoption

At the core of these advancements is AI and machine learning. Nvidia’s involvement with Foxconn underscores how graphics processing units are evolving into robotics enablers. Posts on X from industry figures like Brett Adcock of Figure AI highlight rapid scaling: ‘we plan to ~3x the number of humanoids manufactured in July-Sept,’ indicating a push toward 100,000 generalization-capable robots.

Figure AI’s BotQ facility, described in X posts as ‘the highest volume humanoid production line in the world,’ is initially capable of producing 12,000 units per year, with plans to scale to 100,000. This reflects a broader industry trend where companies are building dedicated factories for robot production, as noted in The Robot Report.

Addressing Labor Shortages and Efficiency

Industries like construction are eyeing humanoids to tackle chronic labor shortages. A McKinsey report, as covered by Robotics & Automation News, suggests deployments could start with simple tasks before expanding over the next decade, potentially boosting productivity in a sector plagued by slow growth.

In manufacturing, the promise is even greater. WIRED proclaims 2025 as ‘the Year of the Humanoid Robot Factory Worker,’ noting that after years in labs, these robots are ready for real-world application, though hurdles like cost and reliability remain.

Challenges in Scaling Humanoid Robotics

Despite the hype, challenges persist. High production costs and the need for advanced AI training are significant barriers. X posts from CCTV+ describe Shanghai’s deployment as a milestone, but emphasize that these robots rely on reinforcement learning, which requires extensive data and testing to achieve reliability.

Moreover, ethical and societal implications loom large. The World Economic Forum warns that while humanoids offer disruption and promise, clear guardrails are needed to manage workforce displacement and ensure safe human-robot interactions.

Innovations in Robot Design and Training

Companies are innovating to overcome these hurdles. Shenzhen LingYiTech, as shared in X posts by CyberRobo, has unveiled workshops for assembling wheeled humanoid robots like AgiBOT A2, transitioning from assembly to mass production testing. This modular approach could lower costs and speed deployment.

Samsung is entering the fray, with plans to build its own humanoid using in-house fabs. An X post from Grishin Robotics quotes Oh Jun-ho stating a prototype would be ‘seen soon,’ positioning Samsung as both supplier and customer in the ecosystem.

Future Implications for Manufacturing

As deployments ramp up, the factory of the future may feature mixed human-robot teams. Built In explains that these robots, equipped with cameras, sensors, and AI, imitate human movements, making them ideal for dynamic production environments.

Analysts predict widespread adoption by 2030. IoT World Today covers ongoing developments, noting that advancements in human-robot interaction are key to scaling. With companies like Foxconn leading, the integration of humanoids could redefine global supply chains.

Economic and Competitive Landscape

The competitive landscape is heating up, with Asia at the forefront. X posts from XMAQUINA highlight Korea and Japan’s shift toward humanoid form factors, with firms like Doosan Robotics and Kawasaki evolving from traditional automation to collaborative systems.

Ultimately, as Humanoid Robotics Technology lists the top 12 humanoids of 2025, the focus is on AI-driven autonomy. This wave of innovation promises to transform manufacturing, but success will depend on balancing technological prowess with practical implementation.