슈나이더 일렉트릭, 엔비디아·HPE, 공정 산업용 물리AI 가속을 위한 전략적 협력 발표

- Introducing the industry's first Industrial AI Agents at the Edge, providing a practical pathway to Physical AI - Built on HPE Private Cloud AI, autonomous AI agents operate directly within industrial environments, continuously monitoring, reasoning, and optimizing operations in real time - Addresses three key barriers to industrial AI adoption at scale: data sovereignty, cybersecurity and AI consumption costs BERLIN, Oct. 22, 2026 (GLOBE NEWSWIRE) -- Schneider Electric, a global energy technology leader, today announced a strategic collaboration with NVIDIA and HPE to accelerate the adoption of Physical AI across process and heavy industries. 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: - Data sovereignty. 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. - Cybersecurity. Increased connectivity can 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. - AI consumption costs. As AI usage grows, cloud-based inference, data transfer and token-related costs can increase, creating challenges 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.