Schneider Electric may not be a household name, but it’s the innovative force behind many of the technologies we use every day, in energy management and industrial automation. The company provides productivity-enhancing and energy efficiency solutions around the world, in homes, building, datacenters, electrical grids, and in nearly every aspect of industry. AI is nothing new to Schneider—it’s been carefully experimenting with and using the technology for more than three decades. Now that the necessary infrastructure and supporting technologies have matured to the point where AI is within reach of all of us, Schneider is ready with its own AI-enabled solutions. The company is basing its customer-facing AI solutions on a highly performant technology from a vendor it has trusted for years: Azure OpenAI Service, a solution within Microsoft Cloud for Manufacturing.
Seeking honest answers to the world’s big questions
Schneider Electric is a digital partner for sustainability and efficiency, and its vast menu of connected devices, solutions, and services confirms this ambition. It builds objects as ubiquitous as circuit breakers for homes—and as extensive as intelligent infrastructure that can transform the energy infrastructure for a city or a country. All the physical products, services, and technology that Schneider provides originate from its core competencies: digitization, electrification, and automation. Its “LifeIsOn” tagline says it all: Schneider provides the insights and technology needed to make the most of the world’s energy and resources.
Perennially pioneering solutions, Schneider has embraced AI capabilities of the solutions within the Microsoft Cloud for Manufacturing: Azure OpenAI Service, Azure Machine Learning, and others. As it uses a whole suite of AI tools to hasten its own innovation and that of its customers, Schneider is exploring answers to some of the most important questions of the day.
Running with AI innovation
To address the most complex and pressing issues, one needs a groundbreaking tool. Recent progress in AI technology has fast-tracked Schneider’s decades of AI exploration with breathtaking speed. “If we take generative AI as an example, it was largely the stuff of research papers as recently as 2017,” recalls Philippe Rambach, Chief AI Officer at Schneider Electric. “Now it’s everywhere. The speed of deployment from research paper to actual usage at scale is incredible.”
His team applies different AI techniques to Schneider’s solutions aimed at sustainability. “One of our own sustainability goals is to reduce carbon emissions. The more complex the process or asset, the more you need AI to take data-based actions to decarbonize it. The AI emphasis is threaded deeply through the company. “Schneider leadership’s message in creating a Chief AI Officer position was clearly that we need to take the technology from the lab to the real world and create impact at scale,” he adds. Yoann Bersihand, Vice President of AI Technology at Schneider Electric, expands on the company’s AI focus. “We didn’t want AI just to be an extra layer on top of the data teams,” he insists. “We decided to really go all-in on AI and not simply create proofs of concepts.”
Partnering with Microsoft to embed AI in productivity solutions
Using Microsoft generative AI technology was a natural progression of a long-standing relationship between the two companies. “We have a long track record of working with Microsoft to build our customer solutions,” says Rambach. “We host them on Azure, so for us, Microsoft Azure AI technologies are the logical next step.”
Bersihand cites other reasons for the partnership. “Like Microsoft, we have customers all over the world,” he says. “We benefit from the presence of Azure datacenter regions throughout the world, and that also helps us to address local regulations and compliance. We would struggle to serve our global customers otherwise.”
Growing customer satisfaction is one of two pillars Schneider follows in its AI innovation use. The other is its commitment to improving internal efficiency to get its innovations to the marketplace quickly.
Schneider is also collaborating with Industry Solutions Engineering (ISE), an organization within Microsoft to co-innovate and co-engineer complex AI solutions that have helped Schneider move faster toward its AI objectives.
Amplifying productivity to push innovation ever higher
Francois Bonnard, AI Partnerships Director at Schneider Electric, recalls how the company’s early AI investigations in the 1980s culminated in its own AI solution. He says, “Generative AI solutions like Azure OpenAI are delivering what I dreamed of when I started my career: seamless cooperative interaction between human and machine to make the best possible decisions.”
Bonnard and his team use that seamless cooperation to boost engineering efficiency with Schneider’s programmable logic controller (PLC) code generation software. Engineers are preparing to use the output of the PLC code generator to rapidly create high-quality, tested, and validated code for PLCs (software that controls robots and other IoT devices in manufacturing). This powerful copilot will automate repetitive tasks and provide intelligent code suggestions that will significantly reduce the time and effort required for PLC programming. This can not only accelerate the development process, but also ensure consistency and adherence to best practices across different projects.
Schneider extends Azure OpenAI Service to boost productivity throughout the organization, with apps like its Knowledge Bot, which helps customer service agents find exactly what they need to answer customer queries. Financial analysts at Schneider use Finance Advisor to support optimal decision making.
“Azure OpenAI is very intuitive to use,” says Julia Peyre, Senior Data Scientist at Schneider Electric. “I don’t have to lose time scrolling through documentation to accomplish my tasks. And it’s up to date with the latest machine language models, so we’re always connected to the latest technology developments.”
Elevating customer successes
Bonnard’s team laid the groundwork for Schneider’s EcoStruxure platform in 2009, well before Internet of Things (IoT) technology was widely known. The solution forms the backbone of the IoT architecture Schneider provides to its customers, based on Microsoft Azure IoT technology. EcoStruxure connects IoT devices on the shop floor to information systems, delivering the insights that drive strategic decision making.
Schneider’s EcoStruxure Microgrid Advisor uses data from multiple sources, enabling dynamic control of a facility’s energy performance. A company can use those insights compared with forecast data to decide, for example, how to use energy from renewables, like solar panels. These energy-optimizing solutions are based on Azure OpenAI Service and Azure IoT. “People are using sustainable energy solutions to both produce and consume energy, and they can optimize how to produce or store that energy on the grid as it makes sense,” says Bersihand. “Without AI, there is no way that we could address a problem as complex as this.”
Another Schneider solution, EcoStruxure Resource Advisor, enables its global customers to optimize energy use over a portfolio of buildings distributed across the globe. In mid-2023, Schneider embedded a companion app in its Resource Advisor: EcoStruxure Resource Advisor Copilot, which makes it easier for customers to understand and manage their energy usage.
“We’re very fortunate to be in this exciting field and to have such an impact,” Bersihand emphasizes. “We use Microsoft AI machine learning services and Azure for our external offers because we believe that our partnership with Microsoft complements our value proposition. It provides the technological backbone that we use to deliver AI at scale. Our industry knowledge complements Microsoft’s technology.”
Bonnard anticipates even further enhancements. He describes how the IoT architecture is built in layers, beginning with the physical products themselves. An intermediate layer handles the local controls, beneath the decision-making layer. “One of the biggest concepts that we anticipate is how to take that decision layer down to the controller level,” explains Bonnard. “Many of our customers cannot, or by policy do not, use the cloud. Putting that AI-enabled decision-making ability down to smaller hardware devices would enable seamless interaction on the plant floor. AI on the edge will be very powerful for those customers.” Bersihand shares his enthusiasm. “Frankly, after 20 years in the software industry, I’ve never felt this level of energy,” he concludes. “With these AI-enabled solutions, we can solve the issues affecting not only industry and bottom lines, but the planet itself.”
