Observing that physical artificial intelligence (AI) represents the next evolution of the technology by enabling machines to perceive, understand and autonomously interact with the real world, a study from Counterpoint Research has found that the global physical AI market is entering a rapid growth phase through advances in robotics, edge computing, generative AI (GenAI), vision technologies and sensor technologies.
The analyst’s Global physical AI market tracker report set out to offer an overview of the rapidly evolving physical AI landscape, tracking device shipments across four core segments – vehicles, robots, drones and AI cameras – and presenting a structured view of how intelligence is moving into the physical world.
It covered a number of autonomous system types that are said to embody spatial sensor-backed AI blended with a digital world. Within robotics, the service, industrial and humanoid segments will make up the bulk of the autonomous systems with embodied AI.
Outlining what he regarded as the current status and potential of the market, Counterpoint principal analyst Soumen Mandal said: “Physical AI represents the next major evolution of AI. While the first AI wave focused on digital intelligence – software that understands text, images and data – the next wave brings AI into the physical world, allowing machines to perceive their surroundings and interact autonomously.”
The study predicted that cumulative physical AI device shipments – including vehicles, robots and drones – will reach 145 million units during 2025-2035. The report believes that service robots will account for the largest shipment volumes in the robotics segment, driven by expanding use cases across logistics, warehouses, hospitality, healthcare, cleaning, security and agriculture.
By contrast, industrial robots, which currently have more limited deployment, are expected to see wider adoption driven by broader applications, improving scale, lower costs and easier deployment models. At present, these devices are largely concentrated in automotive, electronics and heavy machinery industries, where high system costs and complexity restrict volumes.
While recognised as still being in the early stages of development, humanoid robots were seen to be gaining momentum as companies develop machines capable of performing complex human-like tasks across factories, warehouses and service environments.
The study found that Agibot headed the list of vendors with the highest number of annual humanoid robot installations, followed by Unitree, Ubitech, Leju and Tesla. The humanoid robot segment is expected to be the fastest-growing category in terms of shipments, with cumulative installations of humanoid robots projected to exceed 100,000 units by 2028, growing 7x compared with 2025.
Humanoid robots represent one of the most exciting long-term opportunities within physical AI, according to Counterpoint research vice-president Neil Shah. Yet he warned that the industry has to cross a “chasm” from autonomous machine intelligence (AMI) to embodied artificial general intelligence (AGI).
“Advances in GenAI, computer vision systems and motion control are bringing us closer to general-purpose robots that can operate in human environments. While there are advancements in the ‘form’, the ‘mind’ is something that is ripe for innovation,” he added.
Autonomous vehicles – of L4 and above levels of autonomy – were expected to see slower volumes initially, but the expansion of robotaxis and autonomous personal vehicles could significantly scale adoption over time, making this segment the largest revenue contributor from an OEM perspective. This is expected to be fuelled by advanced autonomy, computing, AI capabilities and real-time connectivity.
Commenting on autonomous vehicles, research vice-president Peter Richardson said: “Autonomous vehicles are the foundational layer for the current physical AI transition, and there are lots of similarities between today’s humanoid robot development and autonomous vehicles. However, autonomous vehicles will remain the most value-driven segment fuelled by advanced autonomy, computing, AI capabilities and real-time connectivity.”
Commercial drones – excluding consumer and defence drones – were also expected to see strong cumulative shipment growth due to their relatively lower ASPs and increasingly clear regulatory frameworks in major markets. The report observed that they are emerging as the earliest large-scale deployment of physical AI, with “rapid adoption across logistics, surveillance and enterprise use cases driving high-volume growth”.
The analyst stressed that as physical AI systems scale across industries, collaboration across the OEM, semiconductor, connectivity and software ecosystems will be critical to unlock their full potential. Companies that can build strong platforms and partnerships across the value chain will be best positioned to capture this emerging opportunity.
It added that the rise of vision-language models and vision-action models will unify multimodal perception, language understanding and reasoning and executable control within a single sequence modelling framework, which the report called “a critical inflection point”.
Commenting on opportunities for ecosystem players, research director Marc Einstein said: “Physical AI will create opportunities across the broader ecosystem. Beyond device makers, compute players will benefit by powering the ‘brains’ of these systems. Telecom operators will gain from increased data traffic, connectivity and edge services. Meanwhile, software and services providers will see recurring revenue opportunities through data analytics, lifecycle management, fleet services and cloud infrastructure.”
