Comment by alex43578
16 hours ago
If they're cheap and churnable, they're also the easiest place to see substitution.
Pre-AI, Company A hired 3 copywriters a year for their marketing team. Post-AI, they hire 1 who manages some prompting and makes some spot-tweaks, saving $80K a year and improving the turnaround time on deliverables.
My original comment isn't saying the company is going to fire the 3 copywriters on staff, but any company looking at hiring entry-level roles for tasks that AI is already very good at would be silly to not adjust their plans accordingly.
I mean you're half right. Companies seek to automate some of their transactional labor and reduce their overall head count, but they also want a pool of low paid labor to rotate when they do layoffs, which are usually focused on the highest paid slices of the labor chain.
There's a couple issue with LLMs. The first is that by structure they make a lot of mistakes and any work they do must be verified, which sometimes takes longer than the actual work itself, and this is especially true in compliance or legal contexts. The second is the cost. If a company has a choice to outsource transactional labor to Asia for $3 an hour or spend millions on AI tokens, they will pick Asia every single time. The first constraint will never be overcome. The second has to be overcome before AI even becomes a relevant choice, and the opposite is actually happening. $ per kwh is not scaling like expected.
My prediction is that LLMs will replace some entry level positions where it makes sense, but the vast majority of the labor pool will not be affected. Rather, AI might become a tool for humans to use in certain specific contexts.