At the National University of Singapore (NUS), researchers are advancing electronic skin technology that enables machines to perceive touch, distinguish objects, and even self-repair. These developments mark a shift from earlier skepticism about practical applications to a growing momentum in the robotics and artificial intelligence (AI) sectors worldwide.
In recent years, investment in humanoid robotics has surged, exemplified by Figure AI, a California-based company that raised US$1 billion last September at a valuation of US$39 billion. This single fundraise surpassed a fifth of the US$4.6 billion raised collectively by Singapore startups in 2025. Meanwhile, China has introduced national standards for humanoid robots and aims to deploy 10,000 such robots commercially by the end of this year.
Experts note that creating robots capable of working alongside humans requires more than advanced AI software—it demands integrated systems including sophisticated sensors, electronic skins, joints, and power sources assembled into functional bodies. As large language models and embodied AI develop, they are expected to transform the workforce and economies heavily reliant on knowledge workers, such as Singapore’s, raising questions about how the city-state can maintain its relevance.
Singapore’s current economic strategy advocates leading in AI application rather than pioneering fundamental AI models. However, some experts argue that relying solely on adoption without proprietary technological development risks reducing Singapore to a premium consumer rather than a producer. They propose that Singapore could carve out a critical role by focusing on advanced robotics and semiconductor technologies, particularly in specialized manufacturing niches where smaller countries have historically excelled.
Though Singapore faces limitations in population size, land, and resources, it already produces about 10% of the world’s semiconductors. The government plans to invest S$800 million in the latest national Research, Innovation and Enterprise (RIE) programme to translate semiconductor research into commercial products, emphasizing chip packaging and optical interconnects crucial for robotics and AI data centers.
Achieving global leadership in such areas would require the development of proprietary technologies safeguarded by extensive trade secrets and a rapid, AI-accelerated innovation cycle. Comparisons are drawn to the Netherlands’ ASML, which has invested heavily over two decades to dominate as the sole supplier of critical semiconductor manufacturing equipment, generating high-profit margins and employment growth.
Building a robust ecosystem is also essential. Universities and research institutions in Singapore have made strides in deep-tech research, but translating innovations into commercial ventures demands attracting and nurturing talent, simplifying funding pathways, and fostering collaborations. Initiatives such as the National Graduate Research Innovation Programme, launched in 2025, have equipped hundreds of doctoral researchers with skills to navigate investment processes and intellectual property negotiations, aiming to ease startup formation.
While scaling deep-tech enterprises poses challenges, including the need for patient capital due to long development timelines, institutions like NUS have committed S$150 million toward spinoff companies. Success will be measured not by headline valuations alone, but by how quickly startups progress through funding rounds and bring technologies to market.
As robotics and AI technologies advance, Singapore aims to position itself as a critical hub, balancing innovation with strategic investment and talent development. How effectively it navigates these challenges may determine its role in the global AI-driven economy over the coming decade.