Physical AI: Dynamic Intelligence — A Strategic Guide to Value Capture for AI Entering the Real World

A strategic guide tocapture value as AI 04 03 10 07 Contacts Munich Dusseldorf Tanjeff SchadtPartner,Strategy& Germany+49-151-6733-0436 Jens NiebuhrPartner,Strategy& Germany+49-170-2239-195 About the authors Tanjeff Schadtis a Partner at Strategy& Germany, Munich office, and leads the semiconductorand high-tech business for Strategy& in EMEA. As a member of the technology andtelecommunications practice, he advises clients across the semiconductor, high-tech, software, Jens Niebuhris a Partner at Strategy& Germany and leads the technology and telecommunicationspractice for Strategy& Europe. Jens is also a senior member of PwC’s Global DatacenterCenter of Excellence. Based in the Düsseldorf office, he advises international clients on Andy Ogrinsis a Director at Strategy& US and a member of the technology practice, based inthe Silicon Valley office. He advises clients across the semiconductor, computing infrastructure, Martin Gerhardusis a Senior Manager in Strategy&’s technology and telecommunications practice,based in the Düsseldorf office. With deep expertise in software and electronics, he supports clients Dr. Richard Welleris a Manager in Strategy&’s technology and telecommunications practice, basedin the Düsseldorf office. Combining scientific, academic, and industry experience, he supportsclients in executing complex high-tech transformations across fields ranging from semiconductors Andrea Deubleinis a Manager at Strategy& Germany and part of the technology andtelecommunications practice, based in the Munich office. She applies her strategic technology Cedric Rohmis a Senior Associate at Strategy& Germany based in the Frankfurt office.With his strong background in semiconductor and high-tech projects, he provides clients Matthias Brechtis a Senior Associate at Strategy& Germany working in technology strategy, basedin the Düsseldorf office. Leveraging his background in the semiconductor and high-tech industries,he delivers strategically grounded insights that help clients shape their decisions. EXECUTIVE SUMMARY Artificial intelligence (AI) is entering a new phase. After Generative AI(GenAI) transformed how digital content is created and Agentic AIenabled software systems to plan and act autonomously, the next stepis the extension of AI into the real, physical world. This shift is commonly At its core, Physical AI combines three capabilities: sensing, decision-making, and actuation.But unlike purely digital AI systems, Physical AI must operate under real-world constraintssuch as physics, latency, safety, and reliability. This makes it both significantly more complex ~430bnPhysical AI is expected tounlock a global market of~EUR 430 billion by 2030 Across autonomous driving, industrial automation, logistics, humanoid and service robotics,aerospace and defense, healthcare, and entertainment, Physical AI is expected to unlocka global market of ~EUR 430 billion by 20301, with upside beyond that as systems scaleand mature. Early commercial deployments already exist (such as autonomous vehicles inconstrained domains, warehouse robots, robotic surgery assistance, and advanced inspection Physical AI is not a single product or technology wave – it is a systems transformation. Valuewill accrue not only to companies building robots or vehicles, but also to semiconductorsuppliers, cloud and data center operators, simulation and software platform providers, infra-structure players, and end users who redesign processes around embodied intelligence. In short, Physical AI represents the next major chapter of AI-driven value creation. Theopportunity is real and large, but it will be realized unevenly, through careful orchestrationof technology, economics, and strategy. Understanding this landscape early is becoming Over the next 3 to 5 years, Physical AI is expected totransition from individual pilots to scaled deployments.” Tanjeff Schadt, Partner at Strategy& The Physical AI revolution AI is expanding from software into the physical economyThe defining challenge of today’s AI landscape is not a lack of innovation, but the speed and overlap of progress. In previous technology waves – such as the internet or enterprise soft-ware – capabilities evolved over decades, giving companies time to experiment, standardize, Many organizations are still translating the implications of GenAI – large models that can createtext, images, code, and designs – when the next application class is already gainingmomentum. Agentic AI extends these systems by enabling autonomous planning, tool use,and execution within digital environments. Physical AI represents the next step: AI systemsthat operate in the real world, interacting with physical environments. These developmentsdo not replace one another; they stack and expand the scope of AI. Together, they mark For executives, this creates a growing sense of uncertainty. Which technologies are incremental,and which are structurally transformative? Where should in