Siemens: How Industrial AI Drives Sustainability in Energy

AI and sustainability have become two of the most powerful drivers, challenges and imperatives for industries across the globe. As expectations and urgency grow on both fronts, innovators are discovering ways not only to bring them closer together, but to make them accelerate one another.

With 74% of organisations targeting net zero by 2040, AI is fast becoming core infrastructure for tackling decarbonisation at the necessary speed and scale.

Addressing this dual challenge and opportunity, Siemens has released a report, From Pilots to Performance: How Industrial AI is Helping to Scale Sustainability Impact, produced in partnership with Reuters Events. The study covers 263 senior sustainability leaders, conducted in the third quarter of 2025.

What the numbers show

The report reveals that almost two-thirds of organisations have moved past proof-of-concept into live industrial AI deployments focused on sustainability.

Some 63% have advanced to targeted use, moderate adoption or broad rollout across operations and product development. This growing maturity is now translating into tangible environmental impact.​

Nearly two-thirds of organisations report energy savings averaging 23%, while 59% say they have cut carbon dioxide emissions by an average of 24%.

These results represent strong year-on-year gains compared with 2024, when 41% reported energy savings and 36% reported CO₂ reductions.

“Climate change, biodiversity loss, population growth require customers to embrace energy transition, circularity transition and societal changes at the same time," says Eva Riesenhuber, Global Head of Sustainability at Siemens.

“The complexity of juggling global interconnected system transitions in times of major disruptions can only be mastered with AI.”

Energy management leads the way

Energy management has emerged as the most advanced application area, with 65% of organisations deploying industrial AI solutions in this field. The technology is proving especially effective in optimising energy use across assets and processes, with 52% of respondents citing it as the primary way AI will help reach sustainability targets. Real-world projects highlight the environmental upside.​

In the Netherlands, Alliander – the electricity and gas network operator serving 3.5 million customers – has adopted Siemens’ Gridscale X platform to support the energy transition. The software delivers real-time visibility via a digital twin of the grid, enabling up to a 30% increase in grid utilisation without new physical infrastructure. This added capacity is also allowing more renewable generation to come online.​

Data centres and cooling innovation

In Estonia, Greenergy Data Centers has rolled out Siemens’ White Space Cooling Optimization control system at its site near Tallinn.

The solution uses dense sensor networks to constantly track temperature and airflow, automatically fine-tuning cooling equipment to actual demand.

“When we first launched the system, it improved our efficiency by approximately 30% at the push of a button,” Kert Evert, Chief Development Officer at Greenergy Data Centers, says.

“But this was just the beginning, because the system learns, adapts and improves over time.”

Beyond boosting efficiency, AI is helping to advance circularity and resource productivity. Around 60% of organisations are using AI for resource efficiency management, while 43% apply it to improve waste handling. At the same time, predictive maintenance solutions designed to extend asset life and cut material use have been adopted by 60% of organisations.​

AI for circular product design

At the product level, AI is enabling sustainability criteria to be built into design workflows from day one. Some 63% of organisations report using generative design for physical products, helping teams optimise for material use and embedded carbon at the outset.

Eryn Devola, Head of Sustainability at Digital Industries, a division within Siemens, says AI tools are making sustainable design practical without overwhelming engineering teams.

“It’s now easier to say, ‘While we’re working on this design, let’s also address resource efficiency and carbon footprint.’

“Today, we can model these factors and embed them into decision-making to achieve the right trade-offs without adding major effort for engineering. 

“And we can go further: since we’re already touching the design, we should also explore how to dematerialise, reduce size, increase modularity, etc. 

“These are all key factors that contribute to creating a truly sustainable product for the long term,” she says.

Lighter robotics and cleaner glass

Siemens has showcased these capabilities with lightweight robot grippers produced from a lower-carbon polymer. The grippers weigh under 2kg and account for just 30kg of CO₂ emissions from cradle to gate, versus 670kg for traditional metal grippers weighing close to 50kg. According to the company, upgraded production lines using these components have cut energy use by around half and reduced CO₂ emissions by more than three tonnes.​

Automation Innovation, a specialist in glass production equipment, has also applied AI-powered analytics and digital twin technology to overhaul mould cleaning. The new automated system has saved 700,000 tons of raw materials annually, trimmed on-site energy demand by 30% and avoided nearly one billion kilograms of CO₂ emissions so far, while eliminating the need for hazardous cleaning chemicals.​

Rising confidence in AI’s impact

Confidence in industrial AI as a lever for the energy transition is rising sharply. The share of respondents expecting a high or medium positive impact on accelerating the energy transition climbed from 42% in 2024 to 71% in 2025. Separately, 59% say they are already using AI to help decarbonise operations, according to the Siemens Infrastructure Transition Monitor 2025.​

Brooke Tvermoes, Director of Climate, Energy and Environment at IBM’s Chief Sustainability Office, says: “We implemented AI in our manufacturing operations and the focus was actually to help improve product quality and yield. 

“But by doing that we also reduced waste and energy consumption. That’s a tangible result with real dollar values associated with it, which resonates with people.

“This is important because you cannot choose what challenge you address in the world.

“We talk about decarbonisation, but really we also need to conquer circularity at the same time and we need to keep people and society at the center of our thinking.”

Peter Koerte, Managing Board Member and Chief Technology Officer (CTO) at Siemens, adds: “AI is already transforming how we build and power the world - making it more sustainable every step of the way.”