Microsoft and Schneider: Is Energy's Future Fully Automated?

Schneider Electric and Microsoft, two of the most technologically-innovative companies of the modern era, have struck up a partnership that looks set to make waves in the energy sector.

Together, the firms hope to build the foundations of the next generation of energy systems using the twin powers of AI and automation.

Specifically, Schneider and Microsoft are aiming to cut the cost of hydrogen production, while also optimising energy use and creating a scalable path to digital efficiency.

Across much of the industry, power producers and manufacturing plants still rely on hardware-locked systems that can limit their ability to upgrade or incorporate industrial AI. The two companies hope their collaborative efforts can usher in a newer, simpler, more streamlined era.

A question of energy and industry

The collaboration between Schneider Electric and Microsoft offers a route for energy companies to revitalise operations without large-scale system replacements.

Schneider Electric is a market leader energy technology and energy management. The French firm's EcoStruxure Automation Expert software will play a huge part in this joint endeavour, as it will allow operators to use its applications across new and old assets, regardless of manufacturer.

At the same time, Microsoft provides the digital backbone – cloud, AI and edge infrastructure – for Schneider Electric’s system, connecting insights from field sensors to enterprise dashboards.

Together they have built the Industrial Copilot, an intelligent tool that streamlines the time-intensive tasks of industrial modernisation, from writing control code to automating data capture.

Engineering teams using the system report up to 50% reductions in work time, transforming multi-week projects into hours.

Gwenaelle Huet, EVP of Industrial Automation at Schneider Electric, says: "Every CIO and plant leader asks the same question: can software‑defined automation truly perform under real‑world industrial conditions?

"Industrial leaders don’t need another vision; they need a migration path. Our collaboration with Microsoft and the Industrial Copilot delivers exactly that, proving even the most complex energy systems can run as intelligent, autonomous assets."

Hydrogen and AI

In India, sustainable energy company h2e POWER faced rising costs and inefficiencies in its hydrogen production due to legacy control systems.

Working with Schneider Electric and Microsoft, the company integrated the Industrial Copilot into its solid oxide electrolyser system, creating a continuously monitored and self-optimising hydrogen plant.

h2e POWER’s 20‑kW SOEC unit now operates under autonomous digital oversight, fine‑tuning performance and reducing wear.

More than 6,000 hours of stable operation have already been logged, which speaks to its durability and reliability in high‑demand conditions.

The improvements have lowered overall hydrogen generation costs by up to 10%, equating to around €500,000 (US$584,000) in annual savings for larger facilities.

"Solid oxide electrolyser cells have always offered unmatched efficiency, but true commercial scale depends on sustainable operations, optimised energy consumption, durability, predictive maintenance and remote, autonomous control," explains Siddharth Mayur, Founder and Managing Director of h2e POWER.

“With Schneider Electric’s open, software‑defined automation and Microsoft’s AI capabilities powered by Azure, our systems are becoming smarter, more responsive, safer and dramatically more scalable.

“This open architecture also means we can redeploy intelligence across our entire installed base across multiple locations, without the lock‑in that has constrained industrial innovation for decades.”

Elsewhere, Dayan Rodriguez, Microsoft’s CVP of Manufacturing and Mobility, is optimistic about the road ahead.

“What we’re seeing at h2e POWER shows the future of industrial automation," he says.

"The system is powerful and built to scale. Enterprise dashboards unify data across every site, machine learning improves with every hour of operation, and open standards make the control logic fully portable."