It's a very big "if" because other fields are comparatively underspecified. There's no equivalent to a compiler or interpreter in most cases (with spreadsheets being the lingua franca that comes even close for most industries).
It would "work" but I think it will need even more scrutiny by experts to confirm what's correct and what needs to be re-generated. Please please no vibe accounting.
> Please please no vibe accounting.
Funny you mention; There are multiple companies in Sweden working on AI/ML based accounting. It's not so different from AI/ML based automated driving.
I've seen some of those but all of the ones I've looked at also had a panel of experts who could give it a once-over (or re-work) before sending it back to the client. I'd compare it more to cruise control or driver-assist but not quite automated driving.
Accounting, specifically book-keeping, really plays to the strengths of LLMs - pattern matching within a bounded context.
The primary task in book-keeping is to classify transactions (from expense vouchers, bank transactions, sales and purchase invoices and so on) and slot them into the Chart of Accounts of the business.
LLMs can already do this well without any domain/business specific context. For example - a fuel entry is so obvious that they can match it into a similar sounding account in the CoA.
And for others where human discretion is required, we can add a line of instruction in the prompt, and that classification is permanently encoded. A large chunk of these kind of entries are repetitive in nature, and so each such custom instruction is a long-term automation.
You might have not been speaking about simple book-keeping. If so, I'm curious to learn.