Schneider Electric has been named one of the "Top 10 Most Influential Energy Companies in the World in 2026" by the U.S. news magazine TIME. It was recognized as an energy management company that enhances the operational efficiency of AI infrastructure amidst growing power consumption and cooling demands in data centers due to the proliferation of generative AI.

Schneider Electric Korea announced on the 19th that it was included among the leading companies in the energy sector on TIME's 'TIME 100 Companies: Industry Leaders' list. This year, TIME selected globally influential companies by industry for the first time, comprehensively considering factors such as innovation, sustainability, impact on industrial transformation, and leadership in global markets.

This selection aligns with the trend in which competition in AI data centers is expanding beyond simply securing computational performance to include power supply, cooling, and operational efficiency management. In data centers operating high-performance AI chips on a large scale, stable power distribution and thermal management are emerging as factors determining service stability and cost structure.

Schneider Electric is collaborating with NVIDIA to jointly develop a design guide called 'Blueprint' for data centers operating the latest AI systems. This guide focuses on supporting the efficient design of power supply and cooling structures required for AI chip-based systems.

The company supports the improvement of energy efficiency in industrial sites and data centers based on electrification, automation, and digitalization. The strategy is to enhance both power usage efficiency and sustainability by applying data analysis-based operational technologies to the entire process, from data center design and construction to operation and maintenance.

Olivier Bloom, CEO of Schneider Electric, stated that the importance of data center power and cooling infrastructure is growing due to the proliferation of AI, and announced that the company will support the construction of efficient and sustainable AI infrastructure by integrating power, cooling, and data-driven operational technologies.