True but even for static areas and backgrounds I feel like this detail and fidelity blows away what is used in current AAA games.

I think a bigger problem is how much computational resources NERF models need. From the paper,

"Our model, Mip-NeRF 360, and our 'mip-NeRF 360 + iNGP' baseline were all trained on 8 NVIDIA Tesla V100-SXM2-16GB GPUs."

Even with all that, it takes almost an hour to train. A developer would need to do this for every scene, which may make it unfeasible for indies, those who would benefit the most from NERF in gaming.

The better question is how many person hours would it take to model a scene like that with alternative approaches, and can a NeRF be used to create outputs that could be used in a game engine?

That's basically just FMV games all over again.

Lot of game assets are static, and people are working on animated NERFs too. Also another necessary thing will be collisions and physics.

example for character animation:

https://zju3dv.github.io/animatable_nerf/

example for the static world already working in Unreal engine real-time:

https://www.youtube.com/watch?v=GjpzMDur7UY

diffusion models for NERF asset generation:

https://sirwyver.github.io/DiffRF/

https://dreamfusion3d.github.io/

Physics:

https://www.youtube.com/watch?v=Md0PM-wv_Xg

https://www.youtube.com/watch?v=Eklh1pIAri0

and there are a lot more research being done on this, it's hard to keep up with all the things happening in AI