I think your RE style AI suggestion can be done in the traditional sense of AI in game development; that is, without machine learning involved at all. That's all possible with goal oriented action planning, and similar techniques. Game developers often find though, that making the AI too smart can actually make players dislike playing, or putting completely fair but very smart AI in can make the players report that they feel the AI is cheating or unfair. So it gets dumbed down.
The main issue I see with generative AI and games is that it's all good to be able to chat to an NPC as if it were a person with a personality and knowledge of the world. There's an issue of fidelity though; how can you ensure that the AI only reports things that are true about the game world? And then, the issue of actual behaviour: an LLM might generate speech that has the NPC you're talking to say that they're going off to the inn at 5pm to recruit some sellswords, then march to the den of a fire dragon to defeat it, stopping along the way to collect an ice sword from its guardian maiden who lives in a giant tree nearby. OK, it's to generate that text from the player's prompts, it's very difficult to then actually have the NPCs act out the things that the LLM has just said it would do, tying in pathfinding, scheduling, animation, group behaviour and so on, and carrying out those actions would probably involve more traditional game AI techniques (again, not machine learning) anyway. Maybe that'll be solved some other way, maybe this repo does something like that already, I didn't check.
I'm reminded about how people still talk about how the original F.E.A.R. has the best AI in video games [1], while the actual behavior in a technical sense is quite simple [2] and is fundamentally designed around the player being time-pressured but still understanding what's going on. If you just plug an LLM into everything you lose that intentionality around players understanding the system without actually needing to be a subject matter expert on whatever the enemy should be 'realistically' doing.
You also have to consider how AI techniques fit into the context of a running game. ML techniques haven't really caught on with existing games because they completely tank performance, in a program that has to make computations every frame, in addition to either completely murdering the player or acting weird/being hard to debug or just not being that compelling.
What I've seen of current experiments with integrating LLMs into NPC conversations (I believe someone even got it integrated with a Skyrim mod, iic) is that to skirt around this issue, they just make HTTP requests to OpenAI or whatever. Game runs smoothly, but there's still a weird lag around NPC responses that makes it feel stilted and unnatural, and obviously relies on having a stable internet connection at all times.
It will be exciting to see what people could do with something like a fine tuned local Llama2 model. I don't think the way gpt is set up is very conducive to game systems unfortunately.
The main issue I see with generative AI and games is that it's all good to be able to chat to an NPC as if it were a person with a personality and knowledge of the world. There's an issue of fidelity though; how can you ensure that the AI only reports things that are true about the game world? And then, the issue of actual behaviour: an LLM might generate speech that has the NPC you're talking to say that they're going off to the inn at 5pm to recruit some sellswords, then march to the den of a fire dragon to defeat it, stopping along the way to collect an ice sword from its guardian maiden who lives in a giant tree nearby. OK, it's to generate that text from the player's prompts, it's very difficult to then actually have the NPCs act out the things that the LLM has just said it would do, tying in pathfinding, scheduling, animation, group behaviour and so on, and carrying out those actions would probably involve more traditional game AI techniques (again, not machine learning) anyway. Maybe that'll be solved some other way, maybe this repo does something like that already, I didn't check.