Physical AI startup RealWorld has appointed a North America representative ahead of its H1 2026 robotics foundation model launch. With the physical AI market projected to hit $1 trillion by 2035, capturing the US market is an existential imperative. Founders must navigate extreme capital requirements and geopolitical supply chain dynamics to secure their foothold in this rapidly consolidating space.
The Catalyst: RealWorld’s Strategic US Entry
RealWorld, an emerging player in the physical AI sector, has appointed Carl Choi as its North America representative to accelerate its US market entry. This strategic move is timed perfectly ahead of the company’s highly anticipated launch of a robotics foundation model in the first half of 2026. RealWorld’s objective is clear: to establish robust industrial partnerships and expand its investor network in the world’s most capital-rich technology ecosystem.
This expansion is not merely about geographic growth; it represents a fundamental recognition that the battle for the future of robotics will be won or lost in the United States. With the US AI market projected to reach $201.01 billion by 2026—encompassing enterprise software, cloud infrastructure, and hardware—North America has become the ultimate proving ground for physical AI startups seeking unprecedented scale.
The $1 Trillion Market and the Foundation Model Shift
The physical AI market is currently experiencing a massive inflection point. According to Barclays, physical AI could evolve into a staggering $1 trillion market by 2035, with autonomous systems alone accounting for nearly $500 billion. The global robotics market, currently on a steep upward trajectory, is expected to grow from $124.37 billion in 2026 to $416.26 billion by 2035, reflecting a 14.4% CAGR.
The core technological driver behind this explosion is the shift from task-specific robots to general-purpose “Physical AI” agents. Much like Large Language Models (LLMs) revolutionized software by providing a generalized understanding of text, robotics foundation models aim to provide hardware with a generalized understanding of physics, spatial navigation, and unstructured environments. RealWorld’s H1 2026 timeline places it directly in the crosshairs of this foundation model race. Startups that successfully deploy these models will effectively become the “operating systems” of the physical world.
Geopolitical Arbitrage: Navigating the Hardware Divide
Founders entering the physical AI space must understand the deep geopolitical layer of the industry. Currently, there is a distinct divide between hardware deployment and software/capital concentration. In 2025, approximately 15,000 humanoid robots were deployed globally, but a massive 85% of these were installed in China. The Asia Pacific region as a whole controls 48.7% of the industrial robotics market share.
However, the US dominates the underlying compute infrastructure (exemplified by Nvidia’s staggering $215.9 billion FY2026 revenue projection) and venture capital concentration. RealWorld’s strategy highlights a critical playbook for founders: bridging this gap. Startups must leverage the manufacturing and hardware cost efficiencies found in Asia while aggressively targeting the US market for high-value enterprise deployments, strategic partnerships, and mega-round funding.
Actionable Takeaways for Founders
The physical AI sector is brutally capital-intensive. With projected 2026 spending on physical AI infrastructure ranging from $60 billion to $90 billion, startups cannot afford to make strategic missteps. Here is how founders should navigate this landscape:
1. Secure Vertical Partnerships Before Horizontal Scale RealWorld’s appointment of a dedicated US representative underscores the importance of local, industry-specific partnerships. Even if you are building a “general-purpose” foundation model, initial adoption will be staged. Target manufacturing and logistics first, as these sectors are the most mature for physical AI integration. You need lighthouse customers to prove your model’s efficacy in real-world, unstructured environments.
2. Don’t Reinvent the Infrastructure Do not burn venture capital trying to build custom hardware or compute clusters from scratch. The infrastructure layer is already dominated by giants. Partner with hardware manufacturers for the chassis and utilize existing cloud/GPU providers for compute. Focus your engineering cycles strictly on the orchestration layer, spatial intelligence, and proprietary data collection.
3. Align R&D Milestones with US Capital Cycles Physical AI requires runway that dwarfs traditional SaaS startups. Your technology roadmap (like RealWorld’s H1 2026 model launch) must be tightly synchronized with your US expansion and fundraising efforts. You must demonstrate tangible North American commercial traction to unlock the massive capital required to train next-generation physical AI models.