Artificial intelligence is steadily moving beyond software and into the physical world, where it powers robots, drones, autonomous systems, and smart devices operating in real environments. To help organisations adopt this shift in a more structured and scalable way, EY has announced a new physical AI platform developed using NVIDIA technologies, along with the launch of a dedicated EY.ai Lab and the appointment of new leadership to guide its global physical AI strategy.
The initiative is designed to support companies as they plan, test, deploy, and manage AI systems that interact with the physical world. From industrial robots on factory floors to drones, edge devices, and intelligent machines, EY’s approach focuses on reducing risk and complexity while speeding up enterprise adoption.
A physical AI platform built on NVIDIA technology
At the core of the announcement is EY’s new physical AI platform, which integrates NVIDIA Omniverse libraries, NVIDIA Isaac, and NVIDIA AI Enterprise software. According to EY, this combination provides organisations with a clearer framework for building and operating physical AI systems throughout their lifecycle, from early design to long-term operations.
NVIDIA Omniverse libraries enable the creation of digital twins, allowing companies to build accurate virtual models of real-world systems. These digital environments help teams simulate conditions, test performance, and identify issues before any physical deployment takes place. NVIDIA Isaac adds specialised tools, open models, and simulation frameworks for robotics development, making it easier to design, train, and validate AI-driven robots in detailed 3D settings. NVIDIA AI Enterprise supplies the underlying computing and software foundation needed to support large-scale AI workloads reliably.
EY positions the platform around three connected pillars that are essential for physical AI adoption. The first is AI-ready data, including the use of synthetic data to represent a wide range of physical scenarios that may be difficult, expensive, or unsafe to capture in the real world. The second pillar focuses on digital twins and robotics training, helping organisations connect digital and physical systems, monitor performance in real time, and maintain operational continuity. The third pillar is responsible physical AI, which brings governance, safety controls, ethical considerations, and regulatory compliance into the design process from the beginning.
Together, these elements are intended to help organisations move confidently from experimentation to sustained, enterprise-scale deployment across industries such as manufacturing, energy, consumer goods, and healthcare.
Industry impact and enterprise adoption
EY leaders see physical AI as a major driver of transformation across multiple sectors. Raj Sharma, EY Global Managing Partner for Growth and Innovation, highlights that physical AI is already changing how businesses operate and create value. By increasing automation and improving efficiency, these systems can help organisations lower operating costs while responding to workforce challenges and rising safety expectations. Sharma notes that combining EY’s industry experience with NVIDIA’s AI infrastructure is expected to significantly shorten the path from pilot projects to full production deployments.
From NVIDIA’s perspective, the growing use of robots and automation in real-world settings reflects a broader shift in enterprise priorities. John Fanelli from NVIDIA explains that companies are increasingly turning to physical AI to address labour constraints, improve workplace safety, and enhance productivity. He views the EY.ai Lab, powered by NVIDIA AI infrastructure, as a critical environment where organisations can simulate, optimise, and safely deploy robotics and automation solutions at scale, marking the next stage of industrial AI adoption.
New leadership and the launch of the EY.ai Lab
To support its expanding focus on physical AI, EY has appointed Dr. Youngjun Choi as Global Physical AI Leader. In this role, he will oversee EY’s robotics and physical AI initiatives worldwide and help shape the firm’s advisory capabilities in this rapidly evolving field.
Dr. Choi brings nearly two decades of experience in robotics and artificial intelligence. Before joining EY, he led the UPS Robotics AI Lab, where he worked on digital twins, robotics programmes, and AI tools aimed at modernising large-scale logistics networks. Earlier in his career, he served as research faculty in Aerospace Engineering at the Georgia Institute of Technology, contributing to research in aerial robotics and autonomous systems.
A major responsibility for Dr. Choi is directing the newly opened EY.ai Lab in Alpharetta, Georgia, which is the firm’s first location dedicated entirely to physical AI. The Lab is equipped with robotics platforms, sensors, and advanced simulation tools, allowing organisations to experiment, validate ideas, and build working prototypes before rolling them out in real operational environments.
How organisations can use the new Lab
The EY.ai Lab is designed as a practical, hands-on environment where companies can explore physical AI use cases with reduced risk. Within the Lab, organisations can design and test physical AI systems using virtual testbeds that closely reflect real-world conditions. They can also develop solutions for advanced robotic platforms, including humanoid and quadruped robots, as well as other next-generation machines. In addition, the Lab supports the use of digital twins to improve logistics, manufacturing processes, maintenance planning, and operational resilience.
Joe Depa, EY Global Chief Innovation Officer, explains that clients are increasingly looking for better ways to use technology to improve decision-making and overall performance. He emphasises that physical AI requires strong data foundations and trust to be built in from the start. With Dr. Choi leading the Lab, Depa believes EY teams are moving beyond surface-level experimentation and laying the groundwork for scalable, long-term physical AI operations.
Expanding collaboration and future focus areas
The new physical AI platform and EY.ai Lab build on an existing collaboration between EY and NVIDIA, which earlier introduced an AI agent platform. Looking ahead, both organisations plan to extend their joint work into additional domains, including energy systems, healthcare applications, and smart city infrastructure. There is also a shared focus on supporting automation projects that reduce waste, improve efficiency, and contribute to environmental sustainability.
As physical AI becomes a core part of enterprise transformation, initiatives like this signal a shift toward more responsible, simulation-driven, and scalable adoption. By combining digital twins, robotics, and enterprise-grade AI infrastructure, EY and NVIDIA are positioning themselves to help organisations navigate the complexities of bringing AI safely and effectively into the physical world in 2025 and beyond.
