I think you fundamentally misunderstand how the technology can be used well.
If you are in charge of a herd of bots that are following a prompt scaffolding in order to automate a work product that meets 90% of the quality of the pure human output you produce, that gives you a starting point with only 10% of the work to be done. I'd hazard a guess that if you spent 6 months crafting a prompt scaffold you could reach 99% of your own quality, with the odd outliers here and there.
The first person or company to do that well then has an automation framework, and they can suddenly achieve 10x or 100x the output with a nominal cost in operating the AI. They can ensure that each and every work product is lovingly finished and artisanally handcrafted , go the extra mile, and maybe reach 8x to 80x output with a QA loss.
In order to do 8-80x one expert's output, you might need to hire a bunch of people to do segmented tasks - some to do interviews, build relationships, the other things that require in person socialization. Or, maybe AI can identify commonalities and do good enough at predicting a plausible enough model that anyone paying for what you do will be satisfied with the 90% as good AI product but without that personal touch, and as soon as an AI centric firm decides to eat your lunch, your human oriented edge is gone. If it comes down to beancounting, AI is going to win.
I don't think there's anything that doesn't require physically interacting with the world that isn't susceptible to significant disruption, from augmentation to outright replacement, depending on the cost of tailoring a model to the tasks.
For valuable enough work, companies will pay the millions to fine-tune frontier models, either through OpenAI or open source options like Kimi or DeepSeek, and those models will give those companies an edge over the competition.
I love human customer service, especially when it's someone who's competent, enjoys what they do, and actually gives a shit. Those people are awesome - but they're not necessary, and the cost of not having them is less than the cost of maintaining a big team of customer service agents. If a vendor tells a big company that they can replace 40k service agents being paid ~$3.2 billion a year with a few datacenters, custom AI models, AI IT and Support staff, and totally automated customer service system for $100 million a year, that might well be worth the reputation hit and savings. None of the AI will be able to match the top 20% of human service agents in the edge cases, and there will be a new set of problems that come from customer and AI conflict, etc.
Even so. If your job depends on processing information - even information in a deeply human, emotional, psychologically nuanced and complex context - it's susceptible to automation, because the ones with the money are happy with "good enough." AI just has to be good enough to make more money than the human work it supplants, and frontier models are far past that threshold.