News
Key Takeaways
- AI platform launch. EY introduces a physical AI platform powered by NVIDIA technology.
- Lab and leadership. EY opens a dedicated EY.ai Lab and appoints Dr. Youngjun Choi to lead global robotics strategy.
- Client impact. Enterprise clients in industrials and energy gain structured support for safe, scalable AI deployment.
EY expanded its industrial capabilities Dec. 3 with a new NVIDIA-powered physical AI platform and robotics lab designed to bridge the gap between digital simulation and real-world deployment.
The platform integrates NVIDIA Omniverse and AI Enterprise software to help organizations orchestrate robots and smart-edge devices. Company officials said the solution reduces risk by using digital twins to simulate operations before real-world deployment.
Table of Contents
- EY.ai Physical AI Platform: 3 Key Capabilities
- Physical AI Is Taking Over
- Governance & Data Security Imperatives
- A Look at EY's Background
EY.ai Physical AI Platform: 3 Key Capabilities
The EY physical AI platform focuses on three foundational elements:
- AI-Ready Data: Generates synthetic data to simulate scenarios.
- Digital Twin Creation: Bridges digital and physical worlds for real-time insights.
- Responsible Physical AI: Implements guardrails for safety, ethics and compliance.
Physical AI Is Taking Over
Organizations are rapidly deploying physical AI systems that integrate robotics, digital twins and enterprise data. What leaders anticipated would unfold over a decade is happening now.
Figure’s humanoid robot recently ran 10 hours daily for five months on a BMW production line, marking a shift from demonstration to production. Real-time learning systems now enable machines to interpret physical environments with increasing sophistication.
Leaders face a strategic choice: view robots as labor replacements or redesign entire workflows. Analysts suggest the latter unlocks value by freeing skilled workers for complex, high-value tasks machines cannot perform.
Key deployment considerations include:
- Physical workflow audits to identify repetitive or physically demanding tasks.
- Investment in AI models over hardware for long-term competitive advantage.
- Rapid experimentation within rigorous safety and validation frameworks.
Related Article: The Billion-Dollar AI Lab With No Website: Inside Project Prometheus
Governance & Data Security Imperatives
As AI proliferates across enterprise environments, organizations must address security and compliance. Enterprise-grade AI governance has evolved to manage the risks of agentic systems deployed in physical settings.
Firms implementing these systems report significant gains, including 15% sales increases in retail and 20% reductions in manufacturing downtime through predictive maintenance.
"Physical AI is transforming how businesses across sectors operate and help create value, from enhanced automation and greater efficiency to significantly helping reduce operational costs. By combining deep EY industry knowledge with NVIDIA AI infrastructure, this new platform is expected to accelerate how EY helps clients orchestrate these developments responsibly and support them to take the leap from experimentation to enterprise-scale deployment."
- Raj Sharma
Global Managing Partner – Growth & Innovation, EY
A Look at EY's Background
EY is a global professional services network targeting C-suite executives at large multinational corporations. The firm provides assurance, consulting and strategy services, leveraging data and AI to drive enterprise transformation.
