AI has niches but they’re exactly that: Niches. Small duct tape tasks for fudging over “hard problems” where manual code would result in a worse outcome and take far more time. Little esoteric problem spaces, which notably don’t actually require you to use several states worth of electrical power training on a 50PB dataset of anime titties.
An example: I have a name generator in my game that strings together several consonant+vowel phoneme pairs into a name. This means that the names are always pronounceable, but often the spelling looks really unintuitive. Eg Joosiffe, which the player would likely pronounce as Joseph. However, the leap we do in our head between those two spellings is a process of declassifying phonemes and then re-classifying phonemes, and is actually a “hard problem” from a coding perspective due to the unintituive, multifarious complexities of written, spoken, and conceptualized human language. Adding this step to my name generator in code would be a project of it’s own, larger than the game itself, and wouldn’t ever work nearly as well as it needed to. But relatively small (30MB) AI models that do this with something like 99.8% satisfaction already exist. They didn’t require a data center’s worth of resources to train, and since they’re academic projects they have licenses that allow them to be used for free in a game.
This is a cool use case. Just make sure you retain your own voice! If you read an AI-generated sentence out loud and think “I’d have said it this way instead”, IMO you should absolutely then change it to be that way.