I think the actual answer is more nuanced and less positive. Although I appreciste how many citations your comment has!
I'd point to just oe, which is a really good article MIT's technology review published about exactly this issue[0].
I'd make two overall points firstly to:
> when you have the opportunity to use human labour or AI, AI is almost certainly the greener option as well.
I think that this is never the trade off, AI normally generates marketing copy for someone in marketing, not by itself, and even when if it does everything itself, the marketing person might stop being employed but certainly doesn't stop existing and producing co2.
My point is, AI electricity usage is almost exclusively new usage, not replacing something else.
And secondly on Simon Wilison / Sam Altman's argument that:
> Assuming that higher end, a ChatGPT prompt by Sam Altman's estimate uses: > > 0.34 Wh / (240 Wh / 3600 seconds) = 5.1 seconds of Netflix > > Or double that, 10.2 seconds, if you take the lower end of the Netflix estimate instead.
This may well be true for prompts, but misses out the energy intensive training process. Which we can't do if we actually want to know the full emmisions impact. Especially in an environment when new models are being trained all the time.
On a more positive note, I think Ecosia's article makes a good point that AI requires electricity, not pollution. It's a really bad piece of timing that AI has taken off initially in the US at a time when the political climate is trying to steer energy away from safer more sustainable sources, and towards more dangerous, polluting ones. But that isn't an environment thay has to continue, and Chinese AI work in the last year has also done a good job of demonstrating that AI trainibg energy use can be a lot kess than previously assumed.
[0] https://www.technologyreview.com/2025/05/20/1116327/ai-energ...