← Back to context

Comment by pixl97

1 day ago

As someone who does support I think the end result looks a lot different.

AI, for a lot of support questions works quite well and does solve lots of problems in almost every field that needs support. The issue is this commonly removes the roadblocks from your users being cautious to doing something incredibly stupid that needs support to understand what they hell they've actually done. Kind of a Jeavons Paradox of support resources.

AI/LLMs also seem to be very good at pulling out information on trends in support and what needs to be sent for devs to work on. There are practical tests you can perform on datasets to see if it would be effective for your workloads.

The company I work at did an experiment on looking at past tickets in a quarterly range and predicting which issues would generate the most tickets in the next quarter and which issues should be addressed. In testing the AI did as well or better than the predictions we had made that the time and called out a number of things we deemed less important that had large impacts in the future.

I think that's more the area I'd expect genAI to be useful (support folks using it as a tool to address specific scenarios), rather than just replacing your whole support org with a branded chatbot - which I fear is what quite a few management types are picturing, and licking their chops at the resulting cost savings...