Participants will understand how the convergence of AI, robotics, sensors, digital twins, and edge computing will change physical operations.
The Internet of Things connected machines and collected data. Physical AI adds perception, prediction, planning, and action. Warehouses, factories, vehicles, energy systems, infrastructure, and cities can now respond to changing conditions rather than follow fixed rules. However, when AI leaves the screen, mistakes can damage equipment, interrupt essential services, or put people at risk.
Participants will examine the architecture of a physical-AI system, from sensors and connectivity to models, control systems, and human intervention. Cases will show how these systems support predictive maintenance, autonomous inspection, adaptive logistics, infrastructure management, and human-machine collaboration. Participants will also consider cybersecurity, degraded communications, legacy equipment, and the difference between simulation performance and real-world reliability.
In an interactive design exercise, groups will map a physical operation and identify where intelligence should sit: centrally, at the edge, inside a machine, or with a human operator. They will specify the safe state when data, connectivity, or model performance fails.
This session will be ideal for operations, manufacturing, mobility, infrastructure, and smart-city leaders. Participants will leave able to evaluate physical-AI opportunities as systems rather than isolated devices.
