Ebm‑papst Uses AI to Make Cooling and Ventilation Technology More Efficient

Nominated for the 2026 AI Impact Award in the Product and Customer Experience category 

Stefan Bastian EBM Papst Neo Managing Director
27.03.2026 | Article

The AI Impact Award, presented by the German business newspaper manager magazin and Porsche Consulting, honors companies that successfully and effectively apply artificial intelligence in real-world practice. The award highlights solutions that create genuine economic and societal added value.  

The global industrial and technology leader ebm‑papst, has been nominated for the 2026 AI Impact Award in the Product and Customer Experience category, which recognizes solutions that enhance customer experience while driving profit and revenue growth. In a brief interview, Stefan Bastian, Managing Director at ebm‑papst neo, explains current challenges in energy‑intensive industries, how the AI-driven approach improves efficiency, and the tangible results delivered so far.

 

Mr. Bastian, what are the main challenges companies in energy-intensive industries are facing – and how does the AI solution “Nexaira” address them? 

Stefan Bastian: Companies in energy-intensive industries are confronted with sharply rising and highly volatile energy prices, increasing ESG requirements, and significant pressure from regulations and competition. At the same time, their systems, such as cooling and process systems, are technically complex, often developed over time, and not optimally coordinated. What is frequently missing is transparency across energy flows, and many optimization opportunities remain untapped. This is exactly where “Nexaira” comes in as a holistic digital ecosystem. The solution includes digital services to monitor and optimize the operation of ebm papst’s high-performance fans, as well as AI-based cooling system optimization. This creates the foundation for maximum energy savings, high efficiency, and reliable operational stability. Existing systems can be upgraded cost-effectively through the retrofitting of modern fan technology, software, and sensors. Data centers, in particular, benefit from optimizations based on digital twins.

The digital ecosystem “Nexaira” from ebm papst

The digital ecosystem “Nexaira” includes digital services to monitor and optimize the operation of ebm papst’s high-performance fans, as well as AI-based cooling system optimization – delivering maximum efficiency and energy savings.

The digital ecosystem “Nexaira” from ebm papst
The digital ecosystem “Nexaira” includes digital services to monitor and optimize the operation of ebm papst’s high-performance fans, as well as AI-based cooling system optimization – delivering maximum efficiency and energy savings.

How exactly does the digital ecosystem “Nexaira” help reduce the energy consumption of ventilation and cooling systems?

Through the intelligent interaction of highly efficient fans and a cloud-based, AI-driven control system, our “Nexaira” platform significantly increases the energy efficiency of ventilation and cooling systems. Operating conditions are analyzed in real time and adjusted automatically, ensuring that systems run according to demand and at optimal energy levels. This substantially reduces energy consumption and lowers CO₂ emissions. One key application area is the optimization of cooling systems in data centers. Here, the “Nexaira.Systems” solution uses AI to optimize the control of existing cooling infrastructure in real time, dynamically adjusting operating parameters to changing weather conditions and load profiles. As an AI plug-in, “Nexaira.Systems” can be integrated directly into existing control systems without the need for additional hardware.

 

What measurable economic benefits can companies achieve through the AI-based system optimization?

With our “Nexaira.Systems” solution, companies can achieve significant economic benefits – particularly in data centers. Intelligent, AI-based analysis and automated control optimization can reduce cooling energy consumption by up to 50 percent. According to projections, this corresponds to global savings of up to 128 terawatt hours of cooling energy per year – the equivalent output of 22 nuclear power plants. One of the underlying principles is so-called model predictive control, which continuously analyzes operating data and provides optimized control recommendations. In addition, deviations from simulated operating conditions are detected at an early stage, enabling warnings of potential disruptions or unplanned outages. This lowers operating costs, increases operational reliability, and improves the efficiency of energy-intensive infrastructure. Further savings can be achieved by retrofitting existing systems with highly efficient fans, with investments often paying for themselves within a year.

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