EY is taking a bigger step into the world of physical AI, unveiling a new platform and dedicated lab designed to help companies plan, test, and deploy robotics, drones, and other intelligent devices. The initiative is built on NVIDIA technology and aims to give organisations a clearer path from early experimentation to real-world deployment.
Eugene Demaitre
A structured approach to physical AI
The new platform uses NVIDIA Omniverse libraries, NVIDIA Isaac tools, and NVIDIA AI Enterprise to support everything from robotics design to large-scale AI workloads. EY says this combination allows businesses to model complex environments, validate systems before launch, and manage operations once devices are in the field.
Omniverse libraries allow companies to build detailed digital twins, giving teams the chance to test ideas virtually before committing time and resources. NVIDIA Isaac provides models and simulation frameworks for designing and training robots in realistic 3D environments. NVIDIA AI Enterprise supports the heavier compute tasks needed to run advanced AI systems across devices.
EY has organised the platform around three pillars:
AI-ready data: Synthetic datasets that reflect a wide range of real-world scenarios.
Digital twins and robotics training: Tools that link virtual and physical systems, track performance, and keep operations running smoothly.
Responsible physical AI: Governance and controls built to address safety, ethics, and compliance from the start.
The setup is designed for industries such as manufacturing, energy, consumer goods, and health, where intelligent devices are already becoming part of daily operations.
Raj Sharma, EY Global Managing Partner for Growth and Innovation, says physical AI is already reshaping how companies work. He notes that combining EY’s industry knowledge with NVIDIA’s technology should help organisations move faster from small pilots to full-scale deployment.
NVIDIA’s John Fanelli adds that more enterprises are bringing robots into real-world settings to improve safety and adapt to workforce changes. He says the EY.ai Lab will help companies simulate and optimise these applications before rolling them out.
New leadership and the first EY physical AI lab
EY has appointed Dr. Youngjun Choi as Global Physical AI Leader to guide its strategy. Choi brings nearly two decades of experience in robotics and AI, including leading the UPS Robotics AI Lab and earlier research work at the Georgia Institute of Technology.
Choi will oversee the newly opened EY.ai Lab in Alpharetta, Georgia. It is the first EY facility built specifically for physical AI, equipped with robotics systems, sensors, and simulation environments that allow companies to test ideas and build prototypes before scaling them.
Joe Depa, EY Global Chief Innovation Officer, says clients want stronger tools for decision-making and operational performance. He stresses that physical AI requires solid data foundations and trust. With Choi directing the Lab, he believes EY teams can help organisations move past surface-level concepts and into sustainable, scalable solutions.
At the Lab, companies can:
- Design and test physical AI systems in virtual environments,
- Build solutions for humanoids, quadrupeds, and other advanced robots,
- Improve logistics, manufacturing, and maintenance with digital twins.
This push expands on previous collaboration between EY and NVIDIA, including an AI agent platform introduced earlier this year. Both organisations plan to grow their work into areas such as energy, healthcare, and smart cities, with an emphasis on automation that reduces waste and supports environmental goals.
