Schneider Electric has announced a collaboration with NVIDIA and HPE to develop artificial intelligence (AI) applications for process industries, introducing Industrial AI Agents at the Edge to support operational monitoring, cybersecurity and energy optimisation.
Announced in Berlin, the initiative combines HPE Private Cloud AI, developed with NVIDIA, and Schneider Electric’s operational technology expertise to bring AI capabilities closer to industrial operations.
According to Schneider Electric, the approach is designed to address barriers to wider industrial AI adoption, including data sovereignty, cybersecurity and the costs associated with running AI workloads. Processing data closer to its source could help organisations maintain greater control over sensitive operational information and reduce some cloud-related costs.
The first three AI agents will focus on monitoring operational technology systems, identifying cybersecurity threats and finding opportunities to improve energy efficiency. Schneider Electric said the agents can analyse operational data, assess potential issues and recommend or implement corrective measures, depending on the application.
The companies also plan to use Schneider Electric’s EcoStruxure Industrial Insights applications to help customers deploy, manage and govern multiple AI agents through a single environment.
Schneider Electric said the technology builds on an existing deployment at CMPC Chile, a pulp, paper and packaging producer that has used the company’s Operational Technology Monitoring System (OTMS) for three years to monitor control-system health and availability.
“The next generation of industrial innovation will be driven by intelligence embedded directly into industrial operations,” said Gwenaelle Huet, executive vice president of Industrial Automation at Schneider Electric.
Huet said the collaboration aims to help customers turn operational data into action while improving resilience, efficiency, cybersecurity and sustainability.
The companies said the initiative provides a foundation for more autonomous industrial operations. However, the announcement did not specify a broader deployment timeline or quantify the expected operational or financial benefits.
