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Most AI discussions focus on what AI can do.
I'm more interested in where it still struggles.
From what I've seen, AI handles repetitive work pretty well:
For example, invoice matching is easy until there are partial deliveries, pricing differences, or missing references.
The same thing happens in reconciliation where straightforward matches are simple, but exceptions still need people.
I recently read about account reconciliation automation, and it reinforced that idea. The biggest value isn't replacing people. It's reducing how much repetitive work they have to do before making decisions.
Where have you found AI still falls short?
I'm more interested in where it still struggles.
From what I've seen, AI handles repetitive work pretty well:
- extracting data
- categorizing documents
- matching transactions
- summarizing information
For example, invoice matching is easy until there are partial deliveries, pricing differences, or missing references.
The same thing happens in reconciliation where straightforward matches are simple, but exceptions still need people.
I recently read about account reconciliation automation, and it reinforced that idea. The biggest value isn't replacing people. It's reducing how much repetitive work they have to do before making decisions.
Where have you found AI still falls short?
