AI is moving deeper into the physical world, and EY is laying out a more structured way for companies to work with robots, drones, and other smart devices. The organisation is introducing a physical AI platform built with NVIDIA tools, opening a new EY.ai Lab in Georgia, and adding new leadership to guide its work in this field.
The platform uses NVIDIA Omniverse libraries, NVIDIA Isaac, and NVIDIA AI Enterprise software. EY says the setup gives organisations a clearer way to plan, test, and manage AI systems that operate in real environments, from factory robots to drones and edge devices.
Omniverse libraries support the creation of digital twins so firms can model and test systems before deployment. NVIDIA Isaac tools offer open models and simulation frameworks to design and validate AI-driven robots in detailed 3D settings. NVIDIA AI Enterprise provides the computing base needed to run heavier AI workloads.
EY describes the platform as built around three main areas:
AI-ready data: Synthetic data to mirror a wide range of physical scenarios.Digital twins and robotics training: Tools that connect digital and physical systems, monitor performance in real time, and support operational continuity.Responsible physical AI: Governance and controls that address safety, ethics, and compliance.
The platform is meant to support everything from early planning to long-term maintenance in sectors like industrials, energy, consumer, and health.
Raj Sharma, EY Global Managing Partner – Growth & Innovation, says physical AI is already “transforming how businesses in sectors operate and help create value,” saying that it brings more automation and can help lower operating costs. He says the combination of EY’s industry experience and NVIDIA’s infrastructure is expected to speed up how companies move “from experimentation to enterprise-scale deployment.”
NVIDIA’s John Fanelli notes that more enterprises are bringing robots and automation into real settings to address workforce changes and improve safety. He says the EY.ai Lab, supported by NVIDIA AI infrastructure, helps organisations “simulate, optimise and safely deploy robotics applications at enterprise scale,” which he views as part of the next phase of industrial AI.
New leadership and a dedicated physical AI lab
EY has also appointed Dr. Youngjun Choi as its Global Physical AI Leader. He will oversee robotics and physical AI work and help shape EY’s role as an advisor in this area.
Choi, who has nearly 20 years’ experience in robotics and AI, previously led the UPS Robotics AI Lab, where he worked on digital twins, robotics projects, and AI tools to modernise its network. Before that, he served as research faculty in Aerospace Engineering at the Georgia Institute of Technology, contributing to aerial robotics and autonomous systems.
A key part of his role is directing the newly opened EY.ai Lab in Alpharetta, Georgia – the first EY site focused on physical AI. The Lab includes robotics systems, sensors, and simulation tools so organisations can test ideas and build prototypes before deploying them at scale.
Joe Depa, EY Global Chief Innovation Officer, says his clients want better ways to use technology for decision-making and performance. He adds that physical AI requires strong data foundations and trust from the start. With Choi leading the Lab, Depa says EY teams are beginning to “get beyond the surface of what is possible” and set up the base for scalable operations.
At the Lab, organisations can:
Design and test physical AI systems in a virtual testbed,Build solutions for humanoids, quadrupeds, and other next-generation robots,Improve logistics, manufacturing, and maintenance with digital twins.
The new platform and Lab build on earlier collaboration between EY and NVIDIA, including an AI agent platform launched earlier this year. Both organisations plan to expand their physical AI work to areas like energy, health, and smart cities. They also aim to support automation projects that cut waste and help reduce environmental impact.
See also: Microsoft, NVIDIA, and Anthropic forge AI compute alliance
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