With AI-assisted coding tools, a motivated employee can build a prototype that reads invoices, extracts data and suggests accounting codes in surprisingly little time.
At Telema, we use AI to automate our own work too, and we think people should experiment with it. But there is a big difference between a useful internal tool and a system the finance team depends on every day.
An invoice is not just a document. It contains supplier relationships, negotiated prices, payment instructions, personal data and figures that end up in your financial statements.
Where a prototype stops and real AP work begins
A demo usually runs on a handful of clean invoices. Daily accounts payable looks different:
- A supplier changes its bank account.
- The same invoice arrives twice, once by email and once as an e-invoice.
- A credit note refers to an invoice from a closed accounting period.
- An ERP update breaks the integration overnight.
These are not rare edge cases. They are part of normal AP operations, and every one of them needs a reliable answer before money leaves the company.
What this series covers
This week we look at the questions worth asking before you connect an AI agent to your invoice inbox and ERP:
- Data and confidentiality: where your invoice data goes and who else may use it.
- Attacks and accountability: how invoices can be used to manipulate an AI agent, and who is responsible when it makes a mistake.
- Audit trails and exceptions: what your auditor will ask, and what happens when an invoice does not fit the happy path.
- Cost and ownership: the total cost of a self-built solution and who keeps it running.
None of this is an argument against AI. It is an argument for deciding based on how business-critical the process is, not on how quickly a prototype can be built.
The question is not “Can we build it?” It is “Do we want to operate, secure and audit it for the next five years?“
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