EY and NVIDIA Partner to Help Businesses Deploy Physical AI Solutions

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 Physical AI Platform: Built on NVIDIA Technology

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 — Offers 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 core pillars:

The platform is designed to support everything from early planning to long-term maintenance across sectors including industrials, energy, consumer, and health.

💬 Industry Leaders Weigh In

"Physical AI is already transforming how businesses in sectors operate and help create value — bringing more automation and helping lower operating costs."

— Raj Sharma, EY Global Managing Partner – Growth & Innovation

Sharma adds that the combination of EY's industry experience and NVIDIA's infrastructure is expected to accelerate how companies move "from experimentation to enterprise-scale deployment."

"More enterprises are bringing robots and automation into real settings to address workforce changes and improve safety. The EY.ai Lab helps organisations simulate, optimise and safely deploy robotics applications at enterprise scale."

— John Fanelli, NVIDIA

Fanelli views this as part of the next phase of industrial AI, supported by NVIDIA AI infrastructure at the new EY.ai Lab.

🧠 New Leadership: Dr. Youngjun Choi Appointed Global Physical AI Leader

EY has 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 a strategic advisor in this rapidly evolving field.

Choi brings nearly 20 years of experience in robotics and AI, with a career that includes:

• Leading the UPS Robotics AI Lab, where he worked on digital twins, robotics projects, and AI tools to modernise its global network.
• Serving as research faculty in Aerospace Engineering at the Georgia Institute of Technology, contributing to aerial robotics and autonomous systems.

🏛️ Inside the EY.ai Lab: Alpharetta, Georgia

A key part of Choi's role is directing the newly opened EY.ai Lab in Alpharetta, Georgia — the first EY site focused exclusively on physical AI. The Lab is equipped with robotics systems, sensors, and simulation tools so organisations can test ideas and build prototypes before deploying them at scale.

"Physical AI requires strong data foundations and trust from the start. With Choi leading the Lab, EY teams are beginning to get beyond the surface of what is possible and set up the base for scalable operations."

— Joe Depa, EY Global Chief Innovation Officer

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.

🌍 What Comes Next: Expanding the EY–NVIDIA Partnership

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 into areas such as:

• Energy
• Health
• Smart Cities

They also aim to support automation projects that cut waste and help reduce environmental impact — positioning physical AI not just as a productivity tool, but as a driver of more sustainable industrial operations.