If used in the specific niche use cases its trained for, as long as its used as a tool and not a final product. For example, using AI to generate background elements of a complete image. The AI elements aren’t the focus, and should be things that shouldn’t matter, but it might be better to use an AI element rather than doing a bare minimum element by hand. This might be something like a blurred out environment background behind a peice of hand drawn character art - otherwise it might just be a gradient or solid colour because it isn’t important, but having something low-quality is better than having effectively nothing.

In a similar case, for multidisciplinary projects where the artists can’t realistically work proficiently in every field required, AI assets may be good enough to meet the minimum requirements to at least complete the project. For example, I do a lot of game modding - I’m proficient with programming, game/level design, and 3D modeling, but not good enough to make dozens of textures and sounds that are up to snuff. I might be able to dedicate time to make a couple of most key resources myself or hire someone, but seeing as this is a non-commercial, non-monitized project I can’t buy resources regularly. AI can be a good enough solution to get the project out the door.

In the same way, LLM tools can be good if used as a way to “extend” existing works. Its a generally bad idea to rely entirely on them, but if you use it to polish a sentence you wrote, come up with phrasing ideas, or write your long if-chain for you, then it’s a way of improving or speeding up your work.

Basically, AI tools as they are, should be seen as another tool by those in or adjacent to the related profession - another tool in the toolbox rather than a way to replace the human.