The only artificial driver level limitation on a 4090 that I'm aware of is that P2P (GPU-to-GPU memory access through PCIe) isn't supported. This and NVLink have to do with multi-GPU setups only and even there, not having these features doesn't limit or slow down stuff like multi-GPU LLM inference.
The direct GPU-to-GPU linking is more helpful with AI training however. So if there is a push to drive "AI users" towards workstation GPU's, it's aimed at professionals.
Also, doesn't the pricing make it pretty clear that Nvidia isn't pushing your average Stable Diffusion enjoyer towards a workstation card? I mean, what kind of a hobbyist AI user can afford them?
Getting back to Blackwell, I'll point out that the way AI models are advancing means that during it's lifespan, the 32GB will be much more limiting to the 5090 than the 24GB is/has been to the 4090. The first Stable Diffusion model, released two years ago, was 2GB in size. The current sota T2I model that can be run on a home computer, Flux.1, is 22GB in size.
I would be surprised if Nvidia finds it necessary to gimp the 5090 AI performance in any other way than keeping the current multi-GPU limitations in effect (if even that), the 32GB memory capacity is gimped enough already.