Lots of this is already being done (and using computers to check books balanced predates latest gen AI by some decades). But of course what accountants actually get paid for is tax strategy, edge cases, messy history and talking to authorities (or at least having their stamp of approval on it if the authorities come calling). There's plenty of market for writing software to automate aspects of invoice reconciliation or monitoring accounts for exceptions, but competition already exists...
At the SMB scale accountants are mostly paid to coach/pester/goade the employees to hand in the necessary paperwork in time. The accountants job is relatively quick from there on.
I've been doing this for 20+ years, not with AI but just with code and taking time to understand the important parts of the processes. I still see many companies and especially educational institutions spending way too much manpower on payroll and accounts payable in particular. This is often because of unnecessary bespoke processes that people in the organization believe are necessary and are afraid to change.
This is roughly what my startup is doing, automating financials.
We didn't pick this because it was super technical, but because the financial team is the closest team to the CEO which is both overstaffed and overworked at the same time - you have 3-4 days of crunch time for which you retain 6 people to get it done fast.
This was the org which had extremely methodical smart people who constantly told us "We'll buy anything which means I'm not editing spreadsheets during my kids gymnastics class".
The trouble is that the UI that each customer wants has zero overlap with the other, if we actually added a drop-down for each special thing one person wanted, this would look like a cockpit & no new customer would be able to do anything with it.
The AI bit is really making the required interface complexity invisible (but also hard to discover).
In a world where OpenAI is Intel and Anthropic is AMD, we're working on a new Excel.
However, to build something you need to build a high quality message passing co-operating multi-tasking AI kernel & sort of optimize your L1 caches ("context") well.
My friend works in corporate accounting. He said his company is outsourcing a bunch of accounting functions and laying people off (I don't know the specifics). They are outsourcing to India and the outsourced company is already using AI for stuff compared to his company that isn't. He thinks many companies are going to outsource.
I’m an accountant (CPA, CMA, Big 4), and while there’s some truth in what you’re saying, you’re significantly underestimating the complexity of applying GAAP, or even tax law. What you’re describing is really bookkeeping, not accounting, and there are plenty of tools that already automate that.
There’s a lot of subjectivity in how GAAP is applied and interpreted - creating accruals, deciding when revenue should be recorded, blah blah.
I disagree on this, there are plenty of problems in accounting that an LLM can help with.
I’ve built some software[0] that analyses general ledgers and uses LLMs to call out any compliance issues by looking at transaction and account descriptions.
Is it perfect, nope. But it’s a hell of a lot better than sifting through thousands of transactions manually which accountants do and get wrong all the time.
> But it’s a hell of a lot better than sifting through thousands of transactions manually which accountants do and get wrong all the time.
I still wonder why humans getting things wrong is a problem, but LLMs getting more things more wrong more often than humans never is. At the very least you'll need a human accountant around to verify the LLM. Or I guess you could just practice "vibe accountancy" and hope things work out but that seems like a worse idea than a trained human professional. But I'm probably just a Luddite.
Also, I am admittedly not an accountant, but I don't think they manually sift through every transaction to verify compliance issues in every single case. That probably isn't how that works.
As others have said, the actual accounting part of accounting is pretty well automated already. Spend some time with LLM's, though, and you'll quickly realize their non-determinism is a huge hindrance for this kind of work.
The hard part of accounting, and the part that takes all the time, is the reconciling... which can't be automated.
Everything else has been mostly automated since the 90s.
Accounting rules are also not as discrete as programming. There is a lot of discretion. Accounting is basically law with numbers and is corresponding just as difficult/ impossible for LLMs to master.
Lots of this is already being done (and using computers to check books balanced predates latest gen AI by some decades). But of course what accountants actually get paid for is tax strategy, edge cases, messy history and talking to authorities (or at least having their stamp of approval on it if the authorities come calling). There's plenty of market for writing software to automate aspects of invoice reconciliation or monitoring accounts for exceptions, but competition already exists...
At the SMB scale accountants are mostly paid to coach/pester/goade the employees to hand in the necessary paperwork in time. The accountants job is relatively quick from there on.
> At the SMB scale accountants are mostly paid to coach/pester/goade the employees to hand in the necessary paperwork in time.
The perfect job for AI.
I've been doing this for 20+ years, not with AI but just with code and taking time to understand the important parts of the processes. I still see many companies and especially educational institutions spending way too much manpower on payroll and accounts payable in particular. This is often because of unnecessary bespoke processes that people in the organization believe are necessary and are afraid to change.
This is roughly what my startup is doing, automating financials.
We didn't pick this because it was super technical, but because the financial team is the closest team to the CEO which is both overstaffed and overworked at the same time - you have 3-4 days of crunch time for which you retain 6 people to get it done fast.
This was the org which had extremely methodical smart people who constantly told us "We'll buy anything which means I'm not editing spreadsheets during my kids gymnastics class".
The trouble is that the UI that each customer wants has zero overlap with the other, if we actually added a drop-down for each special thing one person wanted, this would look like a cockpit & no new customer would be able to do anything with it.
The AI bit is really making the required interface complexity invisible (but also hard to discover).
In a world where OpenAI is Intel and Anthropic is AMD, we're working on a new Excel.
However, to build something you need to build a high quality message passing co-operating multi-tasking AI kernel & sort of optimize your L1 caches ("context") well.
My friend works in corporate accounting. He said his company is outsourcing a bunch of accounting functions and laying people off (I don't know the specifics). They are outsourcing to India and the outsourced company is already using AI for stuff compared to his company that isn't. He thinks many companies are going to outsource.
If you look through the documentation for something like Quickbooks, most of what you're discussing is already there.
If you want complex custom rules, and integration with other systems, you're looking at something like SAP.
and there's a huge valley in between of tasks mostly done by humans e.g an A.I negotiate with the tax authority for you - for the amount you owe.
can A.I find some edge case deductions. again people out of their depth about certain fields making authoritative statements.
I’m an accountant (CPA, CMA, Big 4), and while there’s some truth in what you’re saying, you’re significantly underestimating the complexity of applying GAAP, or even tax law. What you’re describing is really bookkeeping, not accounting, and there are plenty of tools that already automate that.
There’s a lot of subjectivity in how GAAP is applied and interpreted - creating accruals, deciding when revenue should be recorded, blah blah.
It is already quite automated to my knowledge.
And it is a very poor fit for moderm LLM based AI. Because accuracy. No mistakes or hallucinations allowed.
I disagree on this, there are plenty of problems in accounting that an LLM can help with.
I’ve built some software[0] that analyses general ledgers and uses LLMs to call out any compliance issues by looking at transaction and account descriptions.
Is it perfect, nope. But it’s a hell of a lot better than sifting through thousands of transactions manually which accountants do and get wrong all the time.
[0] - https://ledgeroptic.com
> But it’s a hell of a lot better than sifting through thousands of transactions manually which accountants do and get wrong all the time.
I still wonder why humans getting things wrong is a problem, but LLMs getting more things more wrong more often than humans never is. At the very least you'll need a human accountant around to verify the LLM. Or I guess you could just practice "vibe accountancy" and hope things work out but that seems like a worse idea than a trained human professional. But I'm probably just a Luddite.
Also, I am admittedly not an accountant, but I don't think they manually sift through every transaction to verify compliance issues in every single case. That probably isn't how that works.
> I still wonder why humans getting things wrong is a problem, but LLMs getting more things more wrong more often than humans never is
Some people hate humanity so much that they cannot wait to replace us all with AI so they never have to interact with another human ever again
That's honestly the only reason I can think that they are so biased toward AI
As others have said, the actual accounting part of accounting is pretty well automated already. Spend some time with LLM's, though, and you'll quickly realize their non-determinism is a huge hindrance for this kind of work.
Most women don't think AI is sexy.
The hard part of accounting, and the part that takes all the time, is the reconciling... which can't be automated.
Everything else has been mostly automated since the 90s.
Accounting rules are also not as discrete as programming. There is a lot of discretion. Accounting is basically law with numbers and is corresponding just as difficult/ impossible for LLMs to master.