[adrr]

Those have been done for 10+ years. We were running sentiment analysis on email support to determine prioritization back in 2013. Also ran bayesian categorization to offer support reps quick responses/actions. Don't need expensive LLMs it.

[doorhammer]

Yeah, I was a QA data analyst supporting three multi-thousand agent call-centers for an F500 in 2012 and we were using phoneme matching for transcript categorization. It was definitely good enough for pretty nuanced analysis.

I'm not saying any given department should, by some objective measure, switch to LLMs and I actually default to a certain level of skepticism whenever my department talks about applications.

I'm just saying I can imagine plausible realities where an intelligent and competent person would choose to switch toward using LLMs in a call center context.

There are also a ton of plausible realities where someone is just riding the hype train gunning for the next promotion.

I think it's useful to talk about alternate strategies and how they might compare, but I'm personally just defaulting to assuming the OP made a reasonable decision and didn't want to write a novel to justify it (a trait I don't suffer from, apparently), vs assuming they just have no idea what they're doing.

Everyone is free to decide which assumed reality they want to respond to. I just have a different default.