Schneider Electric announced a strategic collaboration with NVIDIA and HPE to accelerate the adoption of Physical AI across process and heavy industries. Built on HPE Private Cloud AI, autonomous AI agents operate directly within industrial environments, continuously monitoring, reasoning, and optimizing operations in real time. The deal addresses three key barriers to industrial AI adoption at scale – data sovereignty, cybersecurity and AI consumption costs.
While much of today’s Physical AI conversation is focused on robotics, humanoids and autonomous machines, process industries face a distinctly different challenge. Operators must manage complex, continuous operations where reliability, safety, cybersecurity and energy efficiency are critical to performance. Yet until now, there has been no clear blueprint for how Physical AI can be practically applied across these complex environments.
Schneider Electric, NVIDIA & HPE share a vision to bring AI closer to industrial operations, embedding intelligence directly within the environments where decisions are made and value is created. As an initial demonstration of this vision, the companies are today introducing Industrial AI Agents at the Edge.
The solution combines HPE Private Cloud AI, co-engineered with NVIDIA within the HPE AI Factory with NVIDIA portfolio Schneider Electric’s deep operational technology expertise to enable organizations to securely deploy and scale AI applications at the industrial edge, bringing real-time intelligence closer to critical operations while maintaining control over sensitive data, security and costs.
Many industrial organizations continue to face challenges when scaling AI across operational environments. Requirements around data governance, cybersecurity, operational performance and AI deployment can create barriers to broader adoption.By operating at the edge, the solution helps address three challenges that continue to limit industrial AI at scale. Critical operational data is often too valuable, sensitive or regulated to move beyond operational boundaries. HPE Private Cloud AI provides the secure foundation for Industrial AI Agents at the Edge, enabling organizations to deploy AI close to operations while maintaining control, security and compliance.
Increased connectivity can also introduce additional risk across industrial and critical infrastructure environments. HPE Private Cloud AI reduces the attack surface by keeping and processing the data close to its source.
Cost is the third challenge. As AI usage grows, cloud inference, data transfer and token costs can climb, creating problems for organizations looking to scale AI across sites, assets and operations. Deploying AI at the edge with HPE Private Cloud AI can help reduce some of these costs while providing greater control over where and how AI workloads are executed.
Through Schneider Electric’s EcoStruxure Industrial Insights apps, customers can deploy, manage and govern multiple Industrial AI Agents through a single environment, simplifying lifecycle management, security oversight and maintaining full control of critical operations and infrastructure.
The first Industrial AI Agents focus on operational technology monitoring, cybersecurity and energy optimization. Their practical application can already be seen in industrial environments with companies such as CMPC Chile.
The foundation for this next step is already proven at CMPC Chile, part of Empresas CMPC S.A., one of Latin America’s largest pulp, paper and packaging producers. For the past three years, CMPC Chile has used Schneider Electric’s OTMS in production to monitor the health and availability of control systems across its continuous pulp and paper operations.
OTMS provides CMPC’s teams with a unified view of control systems, servers, workstations and switches, helping specialists identify emerging issues earlier, diagnose problems faster and establish clearer maintenance priorities. This proven deployment demonstrates the value of OTMS as a control-system monitoring solution and provides a strong operational foundation for the future introduction of Industrial AI Agents, with the potential to accelerate investigation and decision-making while keeping people in control of critical action.
The first three Industrial AI Agents at the edge cover OT monitoring, cybersecurity and energy optimization.
OT Monitoring Agents combine real-time operational data, equipment configurations, process topology, alarms, maintenance history and engineering context to understand the physical state of industrial operations. The agents identify emerging issues, reason about likely operational impacts, recommend or initiate corrective actions, and verify that the intervention delivers the expected physical outcome.
Cybersecurity Agents correlate network activity, control system behaviour, asset configurations, operational events and process context to detect abnormal conditions. The agents assess potential impacts on industrial operations, recommend or execute response measures, and validate that systems have returned to a secure and stable state.
Energy Optimization Agents integrate process data, energy consumption patterns, equipment performance, operating conditions and production requirements to understand how energy is used across industrial operations. The agents identify optimization opportunities, recommend or implement adjustments, and verify the resulting impact on energy efficiency, operational performance and sustainability outcomes.
“The next generation of industrial innovation will be driven by intelligence embedded directly into industrial operations,” said Gwenaelle Huet, Executive Vice President, Industrial Automation, Schneider Electric. “While much of today’s focus is on autonomous machines, we see a significant opportunity to apply Physical AI to the industrial systems that power the world’s critical industries. Together with NVIDIA and HPE, we are bringing together expertise in automation, AI and edge computing to help customers transform operational data into action, improving resilience, efficiency, cybersecurity and sustainability while laying the foundation for more autonomous industrial operations.”
“Industrial operations generate vast amounts of data, but turning that data into action remains one of industry’s biggest challenges. By combining NVIDIA Nemotron™ open AI models and HPE Private Cloud AI, a turnkey AI factory solution, with Schneider Electric’s industrial expertise and OTMS platform, Industrial AI Agents can monitor, reason and optimize operations in real time, accelerating the path to Physical AI for process industries,” commented Sri Kodali, Global Head of Developer Relations – Energy and Utilities at NVIDIA.
“Industrial organizations see real opportunities to use AI, and they want to be sure their sensitive data and critical systems will remain protected. Through our collaboration with NVIDIA and Schneider Electric, we’re helping customers use HPE Private Cloud AI to bring AI closer to where their data is generated and decisions are made. This gives customers a way to expand AI use across their facilities while maintaining the security, privacy and control their businesses require,” said Alexia Clements, SVP, Hybrid Cloud Solution Sales at HPE.
“For the past three years, OTMS has helped us improve visibility into the health and availability of our control systems. In continuous industrial operations, identifying issues early is critical to protecting production and avoiding costly disruption. Looking ahead, we see significant potential for AI Agents to build on this proven foundation, helping our specialists investigate issues faster and move more effectively from insight to action, while keeping people in control of critical decisions,” said Matías Jory, Digital & Process Manager, Industrial Operations Vice-Presidency, CMP.
Together, Schneider Electric, NVIDIA and HPE are creating the foundation for the next generation of industrial operations, where intelligent systems can continuously monitor, reason and optimize performance. Over time, these capabilities will help automate the automation, enabling safer, more efficient and increasingly autonomous operations across process industries.
