Finance AI in Finance Departments – How It Really Works

I've seen in many SMEs over recent years how much time simply gets lost in paperwork in finance departments. Typing invoices, pushing receipts, entering numbers into Excel – all stuff that's not only boring but also error-prone in the end. That's exactly where it makes sense to work with smart tools that take over the mundane part.

What's behind "Finance AI" in daily life?

Basically means: Programs that can remember, understand, and automatically execute repetitive work.

In my practice, these are for example:

• Scan, read, and directly post receipts (OCR)
• Automatically suggest correct accounts
• Early warning when something goes wrong with cash flow
• Mark suspicious transactions

Time savings – no theory, real values

Let me give you numbers from companies I've accompanied (matches pretty well with official studies):

Invoice processing

Before: 15–20 min per piece
Now: 2–3 min → 80%+ faster

Month-end closing

Before: almost a week
Now: sometimes finished in 3 days → 60% faster

Reporting

Before: 2 hours of list browsing every morning
Now: 30 min with fresh data → easily 70% time saved

Two examples from Switzerland

Trading company in Zurich – 500+ invoices per month

With OCR + automatic categorization, they now save a good 40 hours per month. After a few weeks, nobody wanted to go back to manual posting.

IT service provider in Bern – infinitely complex project billing

With AI-supported cost allocation, project closings are about 60% faster. Means: invoices also reach customers sooner – important for cash flow.

How we introduce such things

Analysis (1–2 weeks) – look closely at what really eats time.

Pilot (3–6 weeks) – select a tool, first automate only one subprocess. Find errors, adjust.

Rollout (7–12 weeks) – roll out everything, train people, document processes cleanly.

Important learnings from practice

• Clean data is worth its weight in gold – otherwise you're just automating chaos in the end.
• The team must pull together – if accounting thinks AI wants to steal their job, it goes wrong from the start.
• Step by step – better to start small, show success, then expand.

What does it bring to the bottom line?

At a 20-person SME I recently supported:

Before: CHF 15'000 per month for financial processes
After: CHF 2'000 for the tool + about 40% less time effort

Means: almost CHF 4'000 per month less costs – and less stress in the month-end sprint.

My conclusion

Finance AI doesn't replace anyone, but takes away the small stuff from people so more time remains for what really counts – customers, planning, strategy. If you do it smartly, the investment often pays for itself in less than a year.