“Stories and lessons from an unexpected journey in finance.”

If your finance analysts are still doing routine bank reconciliations by hand, you are going to lose your best talent.

For decades, the standard operating model in corporate finance was a brutal 80/20 split: teams spent 80% of their time manually gathering, cleaning, and organizing data, leaving only 20% of their time to actually analyze it.

Today, that model is completely broken. We have officially entered the era of the “Human + Agent” workflow.

With modern AI agents now capable of handling massive data ingestion, spotting historical anomalies, and executing standard reconciliations in the background, the baseline of what it means to be a “good analyst” has fundamentally changed. The AI is doing the heavy lifting, meaning the first draft of your variance report is essentially written before you even pour your morning coffee.

But this does not mean we need fewer humans; it means we need different humans. AI-generated insights are the starting point of the modern finance workflow, not the finish line. The challenge for CFOs is no longer acquiring the technology—it is rapidly upskilling our legacy teams to survive in this new environment.

Here is how you transition your team from data-entry clerks to strategic advisors:

• Train for Interrogation, Not Calculation: Your team no longer needs to hunt for the variance; the AI agent will flag it. Your analysts must be trained to ruthlessly interrogate that output. Why did it happen? Is the AI missing vital market context? Does this actually make business sense?

• Elevate Cross-Functional Communication: When the machines handle the spreadsheets, human value shifts entirely to communication. Your team needs to learn how to walk into the CRO’s office, translate those AI-generated insights into plain English, and negotiate a strategic pivot.

• Embrace Scenario Planning: Instead of spending three weeks building a single static budget, analysts must learn to act as pilots, using AI agents to run dozens of dynamic, real-time “what-if” scenarios as market conditions shift.

If your team’s primary value is simply organizing historical data, they are competing directly with a machine that does not sleep. It is our job as leaders to pull them out of the weeds and teach them how to drive the business forward.

How are you actively training your finance team to work alongside AI agents, and what is the hardest skill to teach them in this new environment?

#TheAccidentalCFO #INERSEC #FutureOfFinance #AIinFinance #CFOPlaybook