As industries seek to blend artificial intelligence with robotics for practical applications, EY—widely known for its consulting services—has launched a dedicated platform for physical AI, appointed a global leader, and opened a new laboratory in Georgia to help clients navigate the complexities of AI-powered systems. The company’s move highlights a strategic investment in enabling smarter automation, with aspirations that reach across manufacturing, logistics, and other sectors. By partnering with NVIDIA and other technology providers, EY aims to address prevalent concerns around data quality and responsible deployment in real-world environments. The new initiatives reflect an increasing industry focus on harmonizing robust AI with safe and scalable operations.
Similar initiatives by EY have focused largely on digital AI and analytics, often within financial and risk advisory domains. Until recently, the company’s collaborations with NVIDIA centered on agentic AI platforms for specific business functions like tax and finance. The new physical AI platform extends EY’s approach from data strategy and financial services to multi-sector robotics, indicating an evolution from digital-only projects to those integrating tangible automation. Meanwhile, the current laboratory launch marks a shift from virtual pilot environments toward hands-on prototyping and deployment, providing an expanded environment for advancing smart robotics at scale.
How Does EY’s Platform Integrate NVIDIA Technologies?
The physical AI platform leverages NVIDIA Omniverse, NVIDIA Isaac, and NVIDIA AI Enterprise software to support the development, simulation, and management of AI-powered robots, drones, and smart devices. EY’s approach centers on producing AI-ready data, employing synthetic data to simulate diverse scenarios before robots reach operational environments. The platform also enables digital twin creation, blending real-time monitoring and analytics to support continuous operations. In addition, EY has prioritized responsible AI by installing operational guardrails for safety, ethics, and resilience throughout the lifecycle of each application.
What Role Does the New Leadership Play?
Dr. Youngjun Choi, taking on the role of EY global physical AI leader, will oversee the expansion of next-generation robotics solutions within the company’s innovation strategy. Choi brings experience from the UPS Robotics AI Lab, where he advanced the deployment of robotics, digital twins, and AI in logistics operations, as well as academic research in aerial robotics at the Georgia Institute of Technology. His responsibilities now extend to leading the EY.ai Lab in Alpharetta, where clients and teams can experiment with and validate physical AI solutions in a controlled, state-of-the-art environment.
“Dr. Choi’s priority is to accelerate the entire physical AI journey for our clients — from early education and immersive demonstrations to building digital twins, generating synthetic data, and driving real industry use cases,”
said Joe Depa, EY’s global chief innovation officer.
How Does the EY.ai Lab Bridge Research and Industry?
Located in Alpharetta, Georgia, the EY.ai Lab gives partners and clients access to robotics, advanced sensors, and simulation technology, supporting rapid prototyping and testing for practical deployments. The lab allows organizations to model and validate concepts virtually before committing resources, and it accommodates research into humanoids, quadrupeds, and other next-gen robotics platforms. Building upon ongoing partnerships, especially with NVIDIA, the lab aims to extend applications to diverse sectors—from energy and healthcare to mobility and smart city infrastructure.
“We’re developing the next generation of EY talent through a hands-on physical AI sandbox where our people can experiment with cutting-edge robotics and AI technologies,”
Depa added.
These coordinated developments showcase EY’s investment in responsibly expanding robotics beyond traditional domains. By integrating comprehensive simulation capabilities, strict governance, and collaborative R&D environments, the company is positioning itself to help industrial clients confront challenges around data reliability, workforce safety, and sustainable operations with AI-powered automation. Unlike digital-only initiatives, the current wave involves the convergence of virtual modeling and tangible deployment, which can shorten innovation cycles and lower upfront risks. For organizations considering adoption, a deliberate focus on high-quality, accessible data and ethical deployment frameworks will be central in realizing practical benefits from physical AI investments. The advancements also signal that partnerships with platform providers like NVIDIA may become more common as firms demand holistic solutions that bridge software, hardware, and regulatory oversight. As the field evolves, practical innovations in simulation, security, and trustworthy AI will likely drive the adoption of robotics across a wider range of industries.
