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Schneider drives AI at US factory edge, EU industrial core

James Blackman
By James Blackman
AI InfrastructureIndustrial AIIndustry 4.0Internet of Things (IoT)IoT

Schneider Electric advances industrial AI with a factory-edge copilot in the US and a sustainable AI data center in Portugal, supporting regional ambitions for smart manufacturing and digital infrastructure.

In sum – what to know:

Factory AI copilots – Schneider launches generative AI assistants with Microsoft to tackle labour shortages and optimise factory performance.

Green AI hubs – It opens a 26MW renewable-powered data centre in Portugal to anchor Europe’s AI infrastructure and digital sovereignty.

Edge-to-core push – New hardware, robotics, and edge AI tools tighten Schneider’s grip from industrial shopfloor to sovereign cloud backbone.

Another industrial tech giant making new inroads with industrial-grade AI: following from Siemens’ claims about specialised agentic AI for Industry 5.0 earlier this week, France-based energy and automation specialist Schneider Electric has issued a couple of notices about new generative AI tooling at the factory edge and new AI infrastructure in municipal sovereign cloud heartlands – to run industrial AI workloads in the US and Europe, respectively, in support of their regional agendas around reindustrialisation and digital build-out. Both initiatives prioritize renewable energy and energy efficiency, and reflect broader industrial realignment around software-defined systems.

At Automate 2025 in Detroit this week, Schneider Electric introduced a new generative AI ‘copilot’ assistant, developed with Microsoft, to help enterprises with labour shortages and skills gaps, as well as complex operations. “Industrial copilots… empower workers by reducing mental strain, providing support, and retaining knowledge despite high [staff] turnover,” it wrote. Otherwise, its new generative AI interface-and-model setup provides recommendations and decisions about industrial systems and processes, as well as troubleshooting and predictive maintenance. It integrates Microsoft Azure AI Foundry with Schneider Electric’s automation solutions.

In Detroit, the firm showed the copilot solution as part of a digital factory demo, based on its EcoStruxure Automation Expert Platform, which also promoted a bunch of software automation tools, next-gen robotics, and motion control tech (see below). Aamir Paul, president of operations at Schneider Electric in North America, said: “Industry must reimagine and redefine what is possible by leveraging the latest technologies… To enhance US competitiveness and address the growing skills gap, the industrial workforce needs new tools. Our copilot… bridges this gap… [and] ensures [teams] can leverage [our] domain expertise to bring systems online faster and optimize them… long-term.”

Separately, across the pond, Schneider Electric has opened a new 26 Megawatt (MW) AI data-centre facility in the coastal town of Sines in Portugal – the first operational site in a brand new 1.2 Gigawatt (GW) development, geared for GPU-intensive workloads. The campus in Sines, managed by “sustainable” AI ecosystem developer Start Campus, is billed as “one of Europe’s largest” core AI venues, positioned as a global data hub, with subsea cable links to North America, Latin America, and Africa, and LATAM, and low-latency connectivity to key European centres. It is one of the only operators in Europe to have fully secured over 1GW of grid power.

Start Campus has secured €8.5 billion of investment into the site, and expects to create 1,200 direct and 9,000 indirect jobs. The SIN01 facility is powered entirely by renewable energy, courtesy of a Power Purchasing Agreement (PPA) designed by the French outfit, which sets “new benchmarks for resilient and sustainable workloads for AI, cloud and GPU clusters”. Schneider has provided all the energy and automation infrastructure, including powertrain and switchgear, medium and low-voltage electrical distribution systems, real-time energy and building management via its EcoStruxure platform, plus remote monitoring, management, and maintenance, and on-site field engineers.

Pablo Ruiz Escribano, senior vice president for Schneider Electric’s ‘secure power and data center’ business in Europe, said: “[The]’ vision to create one of Europe’s largest AI data centre hubs is unprecedented, and we’re honoured to have partnered with Start Campus… to help establish these new foundations at SIN01. This new digital gateway will not only encourage more investment and innovation into the region but ensures hyperscale and cloud providers can leverage world-leading data center capacity to power their AI infrastructure.”

Robert Dunn, chief executive at Start Campus, said: “At Start Campus, we are committed to building the foundation for the next generation of sustainable, AI-ready digital infrastructure. Power is one of the most critical resources in today’s digital infrastructure. But it’s not just about access — it’s about managing power efficiently, intelligently, and sustainably at scale. Our partnership with Schneider Electric transforms the way we operate, integrating world-class energy technology and real-time visibility across every layer of our infrastructure.”

Back to Detroit: the firm’s new products include a motion control system, combining a new industrial PC (IPC) motion controller (Modicon M660) and input/output (I/O) system network terminal slice (NTS; Modicon Edge I/O NTS) for data aggregation, which uses edge computing, AI, and advanced control algorithms to raise efficiency, decision-making, and performance. Besides, it has expanded its Lexium line of industrial robots, going from single-axis to higher-end multi-axis machines, for real-time synchronization and collaboration, and high-speed and -precision positioning in manufacturing and logistics. 

Specifically, its new Lexium MC12 Multi Carrier system affords better moving, positioning, and grouping of objects,and its Lexium Cobot range has been extended with an 18kg payload version and a compact controller. As well, it has showed its AVEVA Enterprise Visualization dashboard for data integration and visualisation, and its TeSys Deca Advanced toolless contactor for motor management (“eliminating the need for tools and crimping, it offers seamless, error-free connections that accelerate installation by up to 75 percent and enable precise, ready-to-robot wiring”, the firm said). The firm claims in a new ad campaign (‘Schmoooth’!) its software and tools afford seven-times better system agility, 10-times faster incident resolution, and… you get the idea.

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ABOUT AUTHOR

James Blackman
James Blackman
James Blackman has been writing about the technology and telecoms sectors for over a decade. He has edited and contributed to a number of European news outlets and trade titles. He has also worked at telecoms company Huawei, leading media activity for its devices business in Western Europe. He is based in London.

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Google Cloud Next shows how network operators and vendors are using AI for telecom

We already know that businesses are pushing hard to figure out how artificial intelligence can benefit them. In telecom specifically, an Nvidia survey earlier this year found that 37% of respondents said their companies were investing in AI for telecom to improve network planning and operations, and 33% said that there had already been investments in AI for telecom field operations.

At this week’s Google Cloud Next event, some of Google Cloud’s specific work on advancing the use of AI for telecom is being highlighted, as well as AI for enterprises in other verticals. Here are three perspectives on how companies are leveraging Google Cloud AI for telecom.

–Verizon has integrated Google Cloud’s generative AI into customer operations, which the two companies said has led to “95% comprehensive answerability for customer inquiries” and “demonstrably more efficient and effective customer care interactions.” Verizon is making use of a Google Cloud conversational AI agent that leverages Google Cloud’s Vertex AI, Gemini models and Agent Assist Panel in order to give its customer service reps “real-time, context-aware, and personalized answers” to customer questions, as opposed to the reps having to do manual searches of knowledge bases.

Verizon has deployed this across 28,000 customer care reps and retail stores. Additional features like automated summaries of conversations, and automated follow-up action reminders, are also in the process of being rolled out. Those internal AI agents are in addition to several genAI tools that are directly customer-facing and use Google’s Gemini models for virtual assistants which use natural language.

Background image: Verizon

“Our collaboration with Google Cloud and the integration of Gemini into our customer care platforms mark a significant advancement in our commitment to providing exceptional customer experiences,” said Sampath Sowmyanarayan, CEO of Verizon Consumer. “The tangible results demonstrate the power of AI to enhance efficiency and empower our customer care teams.”

“The impact of Gemini on Verizon’s customer service operations is a testament to our deep partnership and Verizon’s commitment to continued innovation,” said Thomas Kurian, CEO of Google Cloud. “These results demonstrate the potential of AI to not just improve operations, but to create more meaningful and helpful interactions for customers everywhere, ultimately driving significant value for businesses.”

-“We’re really trying hard to build an autonomous network which is going to be obviously driven by AI more and more over time,” said David Sauvageau, director of software development, data and AI for Bell Canada, in a briefing call prior to Google Cloud Next.

In general, he continued, the network operator see AI as a “fundamental building block for the future of telecom, for innovation, for customer operations and for network operations.”

He said in the short-term, Bell Canada is prioritizing AI applications for telecom which “really focus on optimizing our customer experience and network ops.” For the latter in particular, Sauvageau said, “Our goal is really to leverage all the data that we have available in AI in order to predict and prevent issues before they actually impact our customers. So, really moving from reactive to preventive customer experience.”

Additionally, Sauvageau said, that Bell Canada believes AI is crucial for managing the increased complexity of telecom networks. “We need to be much more efficient, [and have] have faster innovations in areas like edge computing, digital twin, 6G or any other future network technologies. And ultimately … our goal is to build and accelerate the development of our AI-powered autonomous networks.”

-Razvan Teslaru, VP and head of strategy and portfolio for cloud software and services at Ericsson, said that the use of AI for telecom encompasses both increased efficiency and increased monetization—the latter being magic words for the telecom industry right now.

Autonomy is both about enabling differentiated connectivity at scale, he said, and monetization of that differentiated connectivity. At this year’s Mobile World Congress Barcelona, one of the things Ericsson spotlights was how it integrates its service orchestration with Google Cloud and its Vertex AI, Teslaru noted.

It’s now possible, he said, for a user to express their intent in natural language: A request to configure a specific type of connectivity to, say, a hospital, over a dedicated slice. “You can have Gemini interpret that intent and break it into service orders. … Then AI agents can take over these service orders and take them into execution, and also observe the results, so we can take corrective action autonomously,” he said.

So ultimately, then, network autonomy is about delivering personalized (or differentiated) connectivity with efficiency, while also doing so at a scale that means more effective and large-scale monetization.

Google Cloud emphasizes AI agents for telecom

Erwan Menard, director (outbound) of product management for cloud AI at Google Cloud, said that “When we look ahead, we envision networks that can largely manage themselves through the use of intelligent software agents.” He continued: “Think of these agents as digital experts that can automatically handle tasks like network configuration, problem solving and resource allocation.This would free up telcos from any routine operational burden, allowing human experts to focus on innovation and new services, ultimately leading to greater efficiency and productivity in network operations.”

In particular, he emphasized, telecoms face the unique challenge of having a “mission-critical duty to maintain knowledge over technologies which could be in service for decades. So the notion of being able to tap accurately through the knowledge of the company to help onboard a new resource or to assist somebody who has a decision to make—technical or business—is quite an important challenge in the telecom industry.” Google Cloud’s Google Agentspace was designed for such knowledge-heavy industries, Menard continued, to retrieve information across multiple systems with the idea of using “agentic workflows to be able to invest a new way of work.”

This week, the company is spotlighting its a new Agent Gallery, so that employees across the telecom organization can get personalized suggestions on which AI agents would be useful to them—either out-of-the-box from Google Cloud, agents built by the company or third-party AI agents. Google Cloud is also offering the ability to design and build agents with a no-code interface, in which people can essentially walk through a series of steps and “convert that sequence into an agent that then becomes your personalized assistant,” Menard explained.

 

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