Stories and lessons from an unexpected journey in finance.

Every finance leader is feeling the pressure from their CEO or board to “implement AI.” The rush is on to buy the shiniest new FP&A copilot and let the algorithms take over the month-end close.

But here is the dirty little secret the software vendors won’t tell you: If your underlying operational processes are broken, AI will not make you innovative. It will just help you make mistakes at an unprecedented scale.

We are treating AI like a magic band-aid for bad operational plumbing.

The “Garbage In, Garbage Out” Multiplier

Traditional automation is linear. If you build a macro on top of bad data, it breaks, you find the error, and you fix it. AI is different. It is highly capable of looking at your chaotic, unstructured data and confidently telling you a perfectly articulated lie.

If your ERP has fourteen different ways to categorize “software subscriptions,” or if your sales team routinely overrides contract start dates in the CRM to hit quota, an AI tool won’t magically know your true ARR. It will simply synthesize your mess into a beautifully formatted, completely inaccurate dashboard in four seconds flat.

Automating friction is great. Automating structural dysfunction is catastrophic.

Clean House Before You Invite the Robots In

Before you can achieve the AI-driven utopia of instant forecasting and automated variance commentary, you have to do the profoundly unsexy work of data hygiene.

Here is the pragmatic checklist for getting your finance function actually “AI-ready”:

• Standardize the Plumbing: If your General Ledger looks like a junk drawer, stop shopping for AI. Spend the next quarter standardizing your chart of accounts and locking down your GL mappings across all departments.
• Kill the “Shadow” Spreadsheets: You cannot train an AI on your company’s financial reality if the actual business logic lives in a hidden Excel file saved locally on your Controller’s desktop. Bring the logic back into the system of record.
• Audit the Human Exceptions: AI struggles with the “we just do it this way for this one client” workflows. You have to streamline and ruthlessly eliminate your manual exception handling before an algorithm can take over the heavy lifting.

AI is an accelerant, not a savior. If you point it at a well-oiled machine, it will give you unprecedented velocity. If you point it at a chaotic mess, you are just going to hit the wall faster.

What is the most ‘unsexy’ data cleanup project your team had to tackle before you could actually automate a process?

#CFO #ArtificialIntelligence #FPandA #INERSEC #DataHygiene #TheAccidentalCFO