From Digital Twins to World Models: The Next Frontier of Industrial AI

Industrial AI is undergoing a paradigm shift. For years, digital twins — virtual replicas of physical systems — have helped manufacturers simulate factories, optimize production lines, and predict equipment failures. However, these systems are often rule-driven, physics-heavy, expensive to build, and brittle in dynamic environments .

Now, a new class of AI is emerging: World Models — systems that learn physics from data, imagine unseen scenarios, and reason about cause and effect in real-world environments. Often described as the 'GPT moment' for the physical world, these models are already being explored by organizations like NVIDIA, Siemens, Dassault Systèmes, and DeepMind.

In this session, we’ll trace the evolution from digital twins → AI-powered twins → world models , and explore what this shift means for manufacturing, supply chains, and industrial operations. Through real-world case studies, you’ll see how organizations are achieving faster simulations, adaptive systems, and AI-driven industrial intelligence .

This is a strategic, insight-driven session designed to help practitioners and leaders understand how to adopt next-generation Industrial AI systems .

Key Takeaways:

• Digital Twins → World Models Evolution – understand the shift from replication to abstraction, rule-based to data-driven, and passive simulation to active reasoning.
• Industry World Models – how platforms like NVIDIA and Dassault are building persistent, AI-driven representations across the industrial lifecycle.
• Real-World Use Cases – insights from BMW, Siemens, Foxconn, Walmart, and NVIDIA on scaling industrial AI systems.
• The Technology Stack – overview of Omniverse, OpenUSD, State Space Models, and multimodal AI in industrial settings.
• Strategic Playbook – how to evaluate readiness, choose platforms, and build teams for Industrial AI adoption.
• The 2027 Horizon – autonomous factories, simulation-driven robotics, and convergence of world models with agentic AI.

Ankit is a Data Scientist with experience across multiple industries, including roles at Ascentt Systems, Radial Inc, Native Agtech, and Grad Dreams. He focuses on applying AI to solve real-world business problems and building solutions that bridge the gap between technology and business.

He brings a strong ability to connect ideas across domains and communicate complex concepts to diverse audiences, delivering practical and impactful AI solutions.