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A practical guide to automating finance operations in mid-sized companies

Where to start, what to leave alone, and how to measure results when automating finance processes.

Mid-sized companies are often told that AI will transform their finance function. The reality is more modest and more useful: a handful of well-chosen automations can remove most of the manual work, provided the underlying process is sound.

Fix the process first

Automating a broken process just produces errors faster. Before choosing tools, map how the work actually flows: who touches it, where it waits, and which checks genuinely reduce risk. Often you'll find approvals that can be removed and data that is keyed in twice.

Start with high-volume, rules-based work

The best first candidates share three traits: they happen often, they follow clear rules, and errors are easy to spot. Invoice and document extraction, bank and GST reconciliation, and payables workflows usually qualify.

Keep people in the loop

AI tools are good but not perfect. Design every workflow so that low-confidence results and exceptions go to a person for review. Over time, the share of work that needs review should fall.

Leave judgement alone

Credit decisions, vendor negotiations and anything that depends on context should stay with people. Automation should give them better information, not replace their judgement.

Measure before and after

Agree a few measures before you start, such as days to close the month, invoices processed per person, or reconciliation exceptions, and track them afterwards. Results you can show are what earn support for the next phase.

See how our Business Process Re-engineering and AI Implementation services work together.

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