CFOs Now Demand Hard, Auditable ROI from AI—Can Your Beancount Automation Scripts Prove Their Own Value?

General
1

I have been thinking about something that hit close to home this week. A Deloitte report from early 2026 found that 97% of CFOs say their boards now expect regular readouts on AI investment and ROI—not vague “it saves time” hand-waving, but actual numbers: cost savings, productivity gains, faster closes that show up in working capital.

The era of “AI is cool, trust us” is over. As one Accounting Today piece put it, AI in 2026 must “pay for itself like any other capital investment.”

This applies to us too

Now, most of us are not running enterprise AI deployments. But if you have spent any time building Beancount automation—importers, categorization scripts, report generators, reconciliation tools—you have made the same kind of investment. Development time is real. Maintenance time is real. The question is: can you prove the return?

I decided to actually measure mine, and the results were… humbling.

My automation audit

I went through every script in my Beancount workflow and tracked:

Automation Dev Time Monthly Savings Monthly Maintenance Annual Net
Chase CSV importer 6 hrs 45 min/mo 10 min/mo (format changes) +$292
Vanguard investment importer 12 hrs 30 min/mo 30 min/mo (API breaks) -$100
Auto-categorization rules 8 hrs 60 min/mo 15 min/mo +$275
Monthly FIRE dashboard script 20 hrs 20 min/mo 45 min/mo -$583
Tax lot tracking plugin 15 hrs 15 min/mo 5 min/mo -$167

(Using my consulting rate of $75/hr as the opportunity cost baseline)

Two out of five automations have negative lifetime ROI. The FIRE dashboard was by far the worst—I spent 20 hours building it, it saves me 20 minutes a month, and it breaks almost every quarter when Fava updates change something.

The meta-question: tracking automation ROI in Beancount itself

Here is what I find delicious about this problem. You can use Beancount itself to track automation ROI. I set up:

2026-01-01 open Expenses:Automation:Development
2026-01-01 open Expenses:Automation:Maintenance  
2026-01-01 open Income:Automation:TimeSavings

Every time I spend an hour building or fixing a script, I log it:

2026-03-15 * "Auto-categorization rules" "Quarterly maintenance - updated merchant patterns"
  Expenses:Automation:Maintenance    0.5 HOURS {75 USD}
  Assets:TimeBank

Every month I log the estimated savings:

2026-03-31 * "Monthly automation savings" "Chase importer saved ~45 min"
  Income:Automation:TimeSavings    -0.75 HOURS {75 USD}
  Assets:TimeBank

Then a simple BQL query gives me my automation P&L:

SELECT account, sum(convert(position, 'USD')) 
WHERE account ~ 'Automation' 
GROUP BY account

After 3 months of tracking, my automation portfolio is running at about $40/month net positive—but only because the Chase importer and auto-categorization rules are carrying the dead weight of the others.

The honest questions

  1. How many of your automations actually have positive ROI? Be honest—factor in development time, maintenance, and the hours you spent debugging when something broke at 11pm.

  2. Do you track this at all? Or do you just assume “automation = good” and never measure?

  3. Has anyone else tried the meta-approach of using Beancount to track Beancount automation costs?

  4. What is your highest-ROI automation? And your worst?

I suspect most of us are carrying at least one automation that costs more than it saves but we keep it because we enjoyed building it. Nothing wrong with that—but we should be honest about it, especially as the industry moves toward demanding proof over promises.