With power in short supply, data center energy efficiency is now under intense scrutiny. According to Gartner, over 40% of current AI data centers are expected to encounter operational limitations within the next two years. This could jeopardize profitability and competitiveness, forcing operators to either curb their growth or limit workloads.
There’s increasing pressure to ensure every watt is used effectively. Although modern AI accelerators consume more power per chip than earlier versions, they’ve become far more efficient, delivering major improvements in performance per watt for large-scale AI workloads.
These hard-earned efficiency improvements deserve the same level of focus across the entire data center infrastructure. Ensuring uninterrupted operation of AI workloads demands dependable power delivery all the way to the chip. That means every pathway carrying energy from the grid through the facility, along with every system that consumes it, must be carefully examined.
Is data center power architecture now constraining compute capacity? Yes, in brief. When compute capacity outpaces available power, servers remain idle — a costly scenario in data centers packed with premium GPUs that could handle AI workloads but lack the electricity to do so.
When overall capacity is restricted, competitiveness is jeopardized.
