Humans (accountants) are non-deterministic, so unsure if an LLM would be better or worse if we threw more effort at the problem.
But in general, I tend to side with the "lets leave the math to purpose built models/applications" instead of generalized LLMS. LLMs are great if you are just aiming for "good enough to get through next quarter" type results. If you need 100% accuracy, an LLM isn't going to cut it.
Human accountants also have a very important property: liability.
If a certified accountant told me to do X, I'm covered (at least to the point they would assist in recovering, or I can get compensation through their insurance). If LLM tells me, I'm in a bigger problem.
Most small businesses cannot afford CPAs for everyday tasks. At best a CPA signs off on the annual summaries. Most day to day work is done by bookkeepers who are not CPAs.
In my area (Vermont) the going rate for a good CPA is $200/hr. Bookkeepers are $20-30/hr.
Most small businesses also cant afford the risk of current LLMs putting garbage in their books that, in the best case, has to be cleaned up or redone, or, in the worst case, gets the IRS up your ass
Tuned LLMs will become more accurate than bookkeepers for most day-to-day small business transactions. I think you underestimate the amount of errors that normal bookkeepers tend to make.
Well I've seen worse bookkeepers. "You know, you approved of the budget, but where are our customers payments in the balance sheets? We can't find them!" - "Uhm..."
I’m coming back from my accountant right now. He uses winbooks and has interns doing the books. I have no tooling to do it for him, and I’m seeing absurdities such as a 4000 usd refund being processed as cashback, and simple typos not being caught.
I wish I was working with an AI instead of this nonsense. It’d be far more accurate.
God, please, no. Non-deterministic language models aren't the solution to improve bookkeeping.