Networking also becomes a critical factor. Physical AI systems depend on predictable, low-latency connectivity to coordinate sensors and controllers in real time, particularly in factories and warehouses. This can push enterprises to revisit industrial networking designs, with greater emphasis on deterministic performance using technologies such as private 5G, Wi-Fi 7, and time-sensitive networking.
“The result is not cloud displacement, but a rebalance: the cloud serves as the system of learning and coordination, while Arm-based edge and device environments handle real-time perception, decisions, and physical action,” said Manish Rawat, semiconductor analyst at TechInsights.
Steps for CIOs
Preparing for Physical AI requires changes across the technology stack. “IT leaders need to optimize operating systems, AI frameworks, and container platforms for Arm architectures,” Mahapatra said. “Security and lifecycle management for distributed robotics systems must be strengthened. Running pilot projects with Arm-based robotic applications will help validate performance and integration before scaling.”
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