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physical AI robotics

AI's next frontier

Technology 5 min read
AI is moving into the physical world, helping to turn humanoids, self-driving cars and other robotic applications from science fiction to reality.
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AI transforming the physical world

AI has already transformed the digital economy. Its next frontier is more tangible. The technology is being embedded in an increasing number of machines that can sense, move, and operate in a physical space.

Physical AI combines advanced computing models with sophisticated hardware: sensors, actuators (which convert electrical signals into physical motion), processors and machine vision. Together, they create robots and autonomous systems that can operate safely and productively in real environments.

Humanoid robots and autonomous vehicles are the most visible examples of this tech in action. The autonomous vehicle market (including public transport) is estimated to grow to USD 1.2 trillion by 2040, thanks to a compound annual growth rate (CAGR) of 44%.Bank of AmericaAs the technology continues to mature, the rate of adoption is accelerating: the proportion of US rideshare miles completed by robotaxis is forecast to increase from 0.4% in 2025 to 7.5% in 2030. We also expect to see autonomous trucks and public transport, as well as vehicles used in industry, delivery, mining, defence, farming and logistics. That, in turn, will boost the growth of related industries such as mobility as a service (MaaS), software licensing and fleet management. 

Physical AI applications: robots in healthcare and industry

And that is just the very beginning of the transformation we envisage. Many other applications of the technology are already commercially available and highly scalable. According to consultancy PwC, humanoids and autonomous driving will account for only half of the global physical AI market by 2030.https://www.strategyand.pwc.com/de/en/industries/telecommunication-media-and-technology/physical-ai.html

In healthcare, meanwhile, robotic surgery systems illustrate how AI-enhanced robotics can deliver precision, consistency and improved patient outcomes at scale. Robots built by Intuitive Surgical, one of the leading companies in this field, treated more than 3.1 million people worldwide in 2025. With its da Vinci systems, surgeons can use 3D vision and a magnified view to control scissors, scalpels or forceps in robotic hands and perform minimally invasive procedures in areas such as urology.

Applications in industrial settings may be less delicate in nature, but they are equally impactful. Companies like Teradyne are driving the adoption of collaborative robots on factory floors, which can work safely alongside humans, and are also extending AI into tasks such as assembly, material handling and testing. Cobots uncomplainingly take on tasks that are dangerous, dirty or simply dull. Because they do not need light or warmth, they can also help reduce energy use.

Elsewhere, in advanced industrial automation, machine vision is a particularly powerful aspect of physical AI. Suppliers such as Cognex and Keyence provide the “vision and perception” layer that allows robots to understand and navigate complex environments. Their AI-based 2D and 3D vision enables robots to recognise and localise specific parts, inspect quality, and perform pick-and-place and assembly tasks in logistics, warehouses or factories. 

  • 3.1

    million

    patients treated by Intuitive Surgical's robots in 2025

Why physical AI matters: labour, reshoring and productivity

These advances in physical AI come at a very opportune time. Many industries face rising labour shortages due to deep-rooted demographic trends such as ageing populations. The US, for example, faces a labour shortage of some 2 million people by the end of this decade.OECD, Deloitte, FRED, Goldman Sachs Research

As workforces age and labour participation rates plateau, demand for automation rises, with robot density already climbing rapidly in countries like China. Its factories now “employ” over 2 million robots – twice as many as in 2021.World Robotics 2025, https://ifr.org/downloads/press_docs/2025-09-25-IFR_press_release_China_in_English.pdf

Rising labour costs since the early 2000s, particularly in China, further tilt the economics in favour of collaborative and humanoid robots, which can deliver higher productivity and lower long-term unit costs. In markets where productivity growth has stalled, physical AI offers a credible path to re-acceleration.

At the same time, robotics can support the reshoring and regionalisation of supply chains in response to geopolitical tensions and the desire for resilience.

Given this growing demand, it is fortuitous that, as well as improving the robots themselves, AI has also compressed the development cycle. Advanced models enhance data analysis, simulation, and control, enabling faster design, testing and deployment of complex robotic systems.

Opportunities and bottlenecks in robotic advancement

The development of physical AI is not without obstacles. Two bottlenecks stand out: technology and regulation.

Regulators and the public must be convinced that these systems are cost-effective and meet rigorous safety standards.

Hardware and software must become cheaper, more reliable, and safer to support mass deployment, particularly in safety-critical applications like driverless cars or healthcare.

For progress to continue, the industry also needs plentiful supply of semiconductors. While this is a potential bottleneck, it’s also a great opportunity for innovation and growth.

To build more autonomous vehicles, ever more powerful and efficient chips are needed to process vast sensor data streams and make real-time decisions. We believe the automotive semiconductor market has the potential to reach hundreds of billions of dollars over the coming decades.

Analogue and power semiconductor leaders such as Infineon and Microchip provide power management, motor control, sensing and edge-AI chips, which are essential for real-time motion, safety and perception in humanoids and autonomous machines.

Despite all these challenges, the direction of travel is clear: as long as the structural drivers of labour scarcity, reshoring, and rising costs persist, demand for physical AI solutions should continue to build.

Investment insights

Physical AI sits at the intersection of digital intelligence and the physical world. Its progress will be measured not only by spectacular humanoid demos or pilot robotaxi services, but by the steady, compounding adoption of intelligent machines across factories, hospitals, warehouses and cities. For investors willing to look through short-term volatility and focus on the enablers of this shift, the theme offers both diversification and exposure to one of the most tangible expressions of AI’s impact on the physical world.

  • The market for physical AI remains in an early phase, with relatively few pure-play listed companies, especially in humanoids, where many leaders are still private or generate minimal revenue.

  • The managers of Pictet’s Robotics strategy believe that investment in physical AI is best approached through the most innovative part of the value chain rather than solely through end-product manufacturers.

  • The most attractive opportunities today often sit in components, semiconductors, perception systems, and software that serve multiple end-markets – from collaborative robots and robotaxis to industrial automation, medtech and machine vision. Many of these companies are not pure-play physical AI names, but their exposure is rising as AI-enabled hardware becomes an increasingly important part of their business.

This article was originally published in Portfolio Adviser.

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