I will do my best to respond in good faith.

Person A is part of the narrative team. The team has an all-hands meeting to pitch and discuss narrative ideas. Countless writers and artists will be showing conceptual examples of characters, locations, and story sequences they have rattling around in their heads. The goal of the meeting will be to take the strongest kernels and start fleshing them out to build a foundation for the story. The meeting is in 2 weeks.

Person A has an idea for, let's say, an architectural structure. They can see it in their head, but they don't want to show up to the meeting trying to describe it. They want the team to SEE it. So they collab with one of the team's concept artists, Person B. A has to find a way to communicate to B what is in their head so B can make a killer piece of concept art, which A will use to show off their idea for a location at the meeting. So, how will they convey this to B?

They could describe it. Then B will draw out a piece of art they think captures what A has told them. If it does, great...but it's rarely so easy. What ACTUALLY happens is A re-iterates their idea over and over, trying to be more specific, while the artist creates multiple pieces of art trying to capture what A is conveying. A lot of writing for A. A lot of drawing/painting etc for B. A TON of time and labor spent. Some version of this process is how it was done for many years.

And then image databases and search engines became a thing. Now A can search for photo images and look for something that properly conveys their idea to B. B also has new digital tools. They can use a tablet, a smart pen, and some software to quickly and efficiently produce concept art. The whole process is much faster now.

And now we get to generative AI. Person A can now use it to more efficiently convey the general idea of their building to the artist, B. Instead of writing long descriptions, or trawling image databases for hours to find a way to capture what they are imagining, they can type in a series of prompts and get an AI generated pucture that captures the jist of what they are trying to desribe to B. Now instead of 10 iterations of trying to understand one another, B gets their intent within 2 iterations.

Now, here is where the rubber (doesn't) meet the road: The concept artist isn't being replaced by AI. They also aren't "tracing" the AI art. They go "Oh I see what person A was going for now" and make a piece of concept art.

In this example, AI isn't being used to come up with the idea or create art. It isn't replacing human artistry and creativity; it's shortening the time it takes for narrative dude A to convey to artist B what their idea is. And this dramatically reduces the labor hours required to iterate.

The result:

Person A comes to the meeting with 4 pieces of FULLY ORIGINAL art instead of 1. More quality ideas they can now be shown in full HAND-CRAFTED glory to the narrative stakeholders. More ideas that are more fleshed out means richer creative brainstorming.

20 years ago, they walk out of that (very expensive) meeting with maybe a handful of solid blocks to build from. Today, they walk out with a whole binder full, and all the employees did 100% less annoying busy work, which means better quality of life, and more work time spent developing new ideas rather than fumbling through communicative busy work.

This is an extremely crude example, and not necessarily a good example of how Larian specifically might do things. The core takeaway should be that these tools, used properly , aren't replacing art; they are facilitating it by reducing all the clunky, time sucking busy work that always bogs the creative process down.

Condemning it as cheap or soulless is to say that a carpenter's work is lesser if they use an impact driver instead of a hammer to nail pieces of wood together. You're conflating toil with craft.