Software could be the easiest fix for hyperscalers' AI power squeeze, researchers say

Data center energy demand is shooting constantly upwards. By 2030, some 945TWh of electricity is expected to be used to meet AI’s demand; the International Energy Agency believes — that's as much electricity as Japan uses today. The energy crunch is inescapable, and the industry’s answer has largely been to focus on the physical: build more efficient GPUs and secure more power supply from an already tight grid. But is that myopic focus on hardware actually worth it? Instead, could most of the work running on those machines be cut back to save power?

Average power usage effectiveness (PUE) has barely changed for six successive years, according to the Uptime Institute’s 2025 survey. PUE can show whether cooling and power systems are wasteful, but doesn’t account for whether the software running on the servers is doing useful work. …