Putting AI to Work

Monday 8 December 2025

In the current energy transition, the most important metric to follow is how much of yearly global power demand growth can be covered by low-carbon resources. Cold Eye Earth, along with its preceding publications (gregor.us and terrajoule.us), has tracked this metric for over a decade, hoping that this threshold would soon be crossed. But with the exception of a couple of years when total wind and solar grew moderately toward that target, we have continued to wait patiently for a better outcome. (Total global power demand actually fell in the pandemic year, 2020, but the that year remains an unhelpful outlier in all datasets.)

Through the first three quarters of this year, however, reporting indicates that total global demand growth for power is coming in much lower than forecast, which considerably lowers the bar for combined wind and solar to meet all new demand. This is surprising. Not on the wind and solar side of growth, but rather that total growth, which is supposed to be running at 4.00% or so, is coming in lower, reportedly at just 2.7%. Given all the drama and excitement over accelerated AI-driven demand for power, one has to wonder why the high rate forecast, coming from the IEA, for example, is not coming true.

London-based think tank Ember, which tracks this progress, has just reported its latest year-to-date estimate:

In the first three quarters of 2025, solar generation rose by 498 TWh (+31%) and already surpassed the total solar output in all of 2024. Wind generation grew by 137 TWh (+7.6%). Together, they added 635 TWh, outpacing the rise in global electricity demand of 603 TWh (+2.7%).

As previously discussed in the November 10 issue, wind and solar generation growth this year continue to track with the simple (if not simplistic) growth model used by Cold Eye Earth, which projects the two technologies will advance by 775 total TWh this year. But if they have already grown by 635 TWh through Q3, then they may complete the year at a level higher than that projection, above 800 TWh. That’s great news for wind and solar, but also for the Cold Eye Earth model, which may have correctly estimated this year’s growth within 5%.

The big miss here, again, is total demand growth, which is also on pace to come in around 800 TWh—leaving a big gap against the ongoing IEA forecast. In the chart below, Cold Eye Earth previously modeled its usual year-to-year wind and solar growth forecast, and also a three-year run of total demand growth of 4.0% per year. (Note that there are small discrepancies in the comparison of 2024 to 2025’s total demand growth because 2024 was a leap year.)

If total global power demand comes in at just 64% of the forecast this year (800 TWh vs. 1250 TWh), not only will it be a nice illustration of how dominant this factor is to the direction of energy transition, but it will also suggest that much of the expectation of higher growth from AI-related workloads has not yet landed. Other factors that might explain the miss: lower global economic growth as a result of disruptive U.S. trade policies, and there may be weather-related effects too. As we know, extremely hot years can cause global air-conditioning to spike. And any easing of that demand, from an anomalous cool summer, would have the opposite effect. It’s also good to remember that real-time data collection has higher error-risk. After all, even data that’s gathered retrospectively often has to be revised also. (Agencies like the U.S. EIA revise data continually.) So, Ember’s estimate of total demand will likely be revised. But, by how much is uncertain. Finally, there is the forward march of energy efficiency, but that is a small and steady factor and certainly could not account for the huge difference between 2.7% and 4.0% growth of global power.

Progress in AI is pressing onward as a new round of models are released. Google’s Gemini 3 was let loose about three weeks ago and has wowed the tech community with its stellar capabilities. Claude Opus 4.5, from Anthropic, emerged a few days later. And rumor has it that OpenAI—which reportedly sounded the alarm over this mounting competition with a company-wide memo, calling a code red from Sam Altman—has decided to hurry up and release its latest version of ChatGPT this coming week.

Your faithful correspondent thought it might be useful, therefore, to report how these models actually perform on a real-world task. The usual province of Cold Eye Earth is to report, of course, on all the energy demands that might emerge from AI. But there has been so much public focus on that theme that it’s left a deficit of reporting on how AI might work for the average person. In this case, we’ll take a look at how these models handle taxes and financial planning.