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.
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One thing I keep noticing: compared to programming, accounting often looks like the more automatable problem:
It’s rule-based Double entry, charts of accounts, tax rules, materiality thresholds. For most day-to-day transactions you’re not inventing new logic, you’re applying existing rules.
It’s verifiable The books either balance or they don’t. Ledgers either reconcile or they don’t. There’s almost always a “ground truth” to compare against (bank feeds, statements, prior periods).
It’s boring and repetitive Same vendors, same categories, same patterns every month. Humans hate this work. Software loves it.
With accounting, at least at the small-business level, most of the work feels like:
normalize data from banks / cards / invoices
apply deterministic or configurable rules
surface exceptions for human review
run consistency checks and reports
The truly hard parts (tax strategy, edge cases, messy history, talking to authorities) are a smaller fraction of the total hours but require humans. The grind is in the repetitive, rule-based stuff.
And it is a very poor fit for moderm LLM based AI. Because accuracy. No mistakes or hallucinations allowed.
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
How can you disagree with the fact?
Some specific examples (like the one you mentioned, _adjacent_ to accounting per se) don't disprove the main point that 100% accuracy is fundamentally impossible with LLMs, while critical for all key accounting aspects.
Accounting is quite broad and there are many examples of where LLMs can help.
For example, what is tax deductible is subjective to local laws. This is essentially a classification problem that LLMs are particularly good at.