Physical AI Deployments in Manufacturing and Logistics to Reach 400,000 Systems by 2030

A new study by Juniper Research has found that deployments of physical AI systems in manufacturing and logistics will reach 400,000 by 2030, an increase of 3,500% from 2026. This growth is being driven by advances in real-time processing and AI models, which are improving both the capabilities and safety of physical AI operating in real-world environments.

Physical AI systems can perceive, reason, and act in the real world. In manufacturing and logistics, they are expected to play a critical role in improving warehouse and factory efficiency, delivering cost savings for businesses. “Multiple technological advancements are converging to accelerate physical AI adoption,” said Molly Gatford, Senior Research Analyst at Juniper Research. “Reduced latency from improved real-time processing is enabling more reliable real-world operation, while more advanced models allow systems to respond to a broader range of inputs, including tactile data, improving how physical AI interacts with its environment.”

With key technical barriers now being addressed, vendors must move beyond development towards large‑scale deployment of physical AI systems. To do this, vendors must partner with connectivity providers, as reliable, low‑latency connectivity is essential to support real‑time decision‑making, which is vital for physical AI deployment. “Vendors must prioritise connectivity partners that offer edge-enabled connectivity architectures, allowing physical AI systems to process data locally and reduce latency constraints. This becomes essential with advanced physical AI models now requiring processing of data from multiple different sensor inputs,” Gatford concluded.