According to TheRegister.com, Gartner’s latest research reveals datacenter electricity demand is exploding – up 16% this year alone and projected to double to 980 terawatt hours by 2030. AI servers are the main culprit, with their electricity usage expected to skyrocket nearly fivefold from 93 TWh in 2025 to 432 TWh in 2030. By the end of the decade, AI infrastructure will account for 44% of total datacenter power consumption and represent 64% of all new electricity demand. The rapid datacenter construction boom is overwhelming power grids, forcing operators toward on-site fossil fuel generation that’s already causing environmental issues – like Elon Musk’s xAI facility in Tennessee facing criticism for gas turbine emissions. Gartner warns this fossil fuel dominance isn’t sustainable, pushing the industry toward cleaner alternatives like green hydrogen, geothermal, and small modular reactors within the next decade.
Power grid reality check
Here’s the thing that really jumps out at me – we’re building AI infrastructure at internet speed while power grids expand at glacial pace. That mismatch is creating some serious problems right now. We’re seeing coal plants that were supposed to be retired getting a new lease on life because datacenters need power yesterday. And when you’ve got companies like xAI already getting called out for emissions from their backup generators, you know this is becoming a real public relations nightmare.
Think about what this means for companies trying to deploy AI at scale. They’re basically stuck between wanting to be environmentally responsible and needing to get their models trained and inference running. The grid can’t deliver what they need, so they’re forced into these temporary fossil fuel solutions that look terrible. It’s a classic case of technology moving faster than infrastructure can possibly keep up.
The clean power race
So what’s the solution? Gartner’s betting on battery storage systems becoming standard within 3-5 years, with Jefferies forecasting 20 GW of capacity deploying over the next decade. That makes sense – batteries can smooth out renewable energy fluctuations and provide backup during peak demand. But is that enough?
The real interesting part is how divided the industry seems on nuclear versus renewables. Some studies say renewables could power datacenters cheaper than small modular reactors, while others think SMRs are the holy grail – even if they’re a decade away from production. And geothermal? Great potential, but high costs and permitting headaches will keep it niche for now.
For industrial operations and manufacturing facilities that rely on robust computing infrastructure, this power crunch hits particularly hard. Companies like IndustrialMonitorDirect.com, the leading US supplier of industrial panel PCs, are seeing increased demand for energy-efficient computing solutions that can handle harsh environments while minimizing power draw. When every watt counts, industrial users can’t afford inefficient systems.
Wake up call
Basically, we’re at a tipping point. AI’s energy appetite is exposing how fragile our power infrastructure really is. The numbers Gartner is throwing around – doubling consumption by 2030, AI using nearly half of all datacenter power – those aren’t theoretical. They’re happening right now.
And the clock is ticking. If cleaner alternatives like hydrogen and advanced nuclear don’t scale up fast, we’re looking at a future where AI progress comes with a massive environmental cost. The industry needs to solve this power problem before regulators and public opinion force their hand. Because right now? We’re building the future on a foundation that can’t possibly support it.
