Unfortunately, most estimates of LLM energy use are somewhat out of date due to the rise of reasoning models. A small amount of personal usage is probably still not that energy intensive, but I don't think it's negligible anymore. 

The most up-to-date estimates I've seen of AI energy use is this paper here. I recommend you look at table 4. For the o3 reasoning model, which is probably the closest analogue to todays reasoning models, a short query costs something like 7 Wh, a medium query is 20 Wh, and a long query is 30 Wh. Using a non-reasoning model like GPT-4o was much less intensive at like 0.4 Wh for a small query, however in my experience the results tend to be a lot worse. 

So if you end up using like 10 medium queries to a reasoning model over the course of a project, that would add up to 0.2 kWh: if you use 100 queries, that would be 2 kWh.  The typical household energy use is something like 30 kWh per day. So the impact is small, but non-neglible: probably there are other things you can do that will have a bigger impact on energy use. 

Personally, I would be worried about cognitive offloading: I think that an overreliance on AI can hamper your ability to learn things, if you offload mentally difficult tasks to the AI.