IT in Manufacturing


AI accelerates energy transformation

May 2025 IT in Manufacturing

With the rapid expansion of generative AI applications, data centre power demand is reaching unprecedented levels. According to a Cushman Wakefield report, AI-related data centre revenue is expected to increase 8,8 times by 2028 compared to 2024. However, AI servers consume five to ten times more power than traditional servers, especially during AI model training where energy consumption surges. This exponential demand raises critical concerns about whether traditional centralised power grids can continue to support AI-driven data centres. Nations and industries worldwide are facing increasing power scarcity challenges while data centres must also comply with energy efficiency and clean energy policies, further straining electricity supply.

Tech giants investing in diverse energy sources to secure power supply

To ensure a stable power supply for AI operations, major cloud and technology companies are making substantial investments in energy infrastructure. Microsoft and Google are actively exploring nuclear energy technologies to secure stable and efficient power sources, reducing their reliance on traditional power grids. Meanwhile, Amazon is investing heavily in clean energy initiatives, including large-scale solar and wind power projects complemented by energy storage solutions. These efforts aim to stabilise AI data centre operations during peak demand periods while mitigating risks associated with grid instability.

Transitioning from backup power to hybrid energy management

Traditionally, data centres relied on N+1 or 2N+1 backup power systems to ensure operational stability in the event of single or multiple failures. However, as AI workloads push power consumption to unprecedented levels and as diverse energy technologies emerge, data centres are shifting from traditional backup power strategies to hybrid energy management. By integrating advanced smart grids and microgrid technologies, data centres can dynamically allocate power resources, optimising energy efficiency. AI-driven energy management systems further refine power distribution strategies, reducing waste, enhancing operational performance and enabling more flexible energy deployment.

The future of AI data centres: Embracing hybrid energy and sustainability

Next-generation AI data centres will adopt more flexible and efficient power supply models. Hybrid energy infrastructures will become the standard, combining traditional power grids, renewable energy and energy storage solutions to ensure reliability while pursuing carbon neutrality. However, this transformation presents new challenges such as integrating multiple energy sources, enhancing power infrastructure monitoring, improving data communication efficiency and refining energy management strategies. As advancements in smart grids and clean energy technologies continue, AI data centres are poised to enter an era of high efficiency and low carbon emissions, providing a stable and sustainable power foundation for global AI computing.


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