What are the major flaws with automating finance and accounting operations compared to sales and marketing functions when using AI?
The main problem with automating finance is the risk of costly mistakes. If an automation glitches and adds extra zeros to an invoice or payroll, you can instantly create a huge loss—think turning a $1,000 payroll into $10,000, which dwarfs the modest time savings. The marginal benefits of automation in finance are small, while the potential downsides are massive, especially when the automation interacts with bank accounts. For example, automating payroll for ten staff might save only 40 minutes a month, which translates to about $15 in savings—hardly worth the risk of a $99,000 error. Instead of fully automating, I recommend doing the heavy‑lifting manually, then using a simple queue to batch payments (e.g., calculate amounts, then push transactions through Wise once or twice a month). You can also leverage AI for tasks like parsing financial statements, generating cheap analysis packages, or automating bookkeeping, but keep the core financial actions under human control because the juice is often not worth the squeeze.
You can automate many finance and accounting tasks—like categorizing transactions, variance analysis, and building dashboards—but if you’re creating a regulated financial product you must comply with relevant regulations (though I don’t recall the exact U.S. body). I avoid highly regulated industries like medical or finance because I don’t want to deal with that compliance burden; I stick to the B2B agency space where it’s more ‘wild west’. For most businesses, the limitation isn’t the automation itself but data‑security concerns; however, the onus of due diligence is on the company hiring you, not on you as the provider. You can still add value by using AI to spot large expenditures or strange transactions in QuickBooks or Xero exports, or to categorize bulk transactions, without trying to compete directly with those platforms.
When you jump on the call with a larger bookkeeping client, start by asking what prompted them to meet—this reveals their motivations and curiosity about AI automation. Then request a walk-through of their typical customer journey, from first brand encounter to the last conversation, and listen carefully. Compare what they say they want with how their customers actually interact with their business. Most sizable bookkeeping firms still have inefficient processes that scale by hiring more people, yielding low revenue per staff ($10k-$20k). By spotting these low-hanging fruit—arbitrage opportunities where AI can automate manual steps—you can show how moving to a model where revenue per staff reaches $100k (capping at four or five clients per person before needing another hire) creates massive value. In short, diagnose their goals, map their journey, uncover inefficiencies, and position your AI workflow as the lever that dramatically boosts their productivity and profitability.
Using AI for accounting is a bad idea—high downside risk, low upside. Just pay your accountant a few extra hundred dollars a month; bookkeeping is cheap. Instead, focus your effort on the top of funnel: get more eyeballs, more bookings, improve the reservation follow‑up, and collect more five‑star reviews. That’s where you’ll generate hundreds of thousands of dollars in opportunity cost, not a few hundred from bookkeeping. If you still want a bookkeeping system, log every card transaction via Plaid or API into a chart of accounts and export to a spreadsheet or QuickBooks.
It’s very difficult to know whether to stick with CRO or test AI automation without knowing your revenue or how long you’ve been at it. At the end of the day, those are the only two variables that matter for deciding whether to keep doing something or move on. If you’re asking this question, you’re likely not achieving the results you expected; that could be due to your expectations or your actual performance relative to reasonable expectations. AI automation is a solid niche, but CRO is directly defensible from a revenue perspective. Imagine a company making $100,000 a month with their CRO. If you offer to double their CRO, you’re offering an additional $100,000 per month because their funnel is their only revenue source. At $100,000 a month, you can charge 10‑15% as a service provider, yielding $10,000‑$15,000 per month from that client alone. All else equal, that’s a 7‑10x ROI—a strong offer right out of the gate. You can pair it with a fixed‑price guarantee (e.g., guarantee X improvement in conversion rate or you don’t pay, money‑back, free landing page) to get them in the door, improve CRO, and move to a longer‑term, performance‑based relationship. I don’t think CRO is a bad niche, nor is it at risk of being automated away; automation or AI would actually let you do more with it. The fact you’re asking this suggests you’re doing something wrong. Specific strategies: How many customer contacts are you making per day? Are you contacting and selling to at least 100 people daily for this service? If not, and you haven’t done that for 90 days straight (≈9,000 contacts), keep going until you hit that mark. After about 9,000 contacts you’ll have a reasonable sense of how it works. If you can’t do it, can’t hack it, or just suck at it, there’s no shame in moving on to something that works. I believe AI automation is probably the best service‑based business model to start, which is why I teach it in Maker School (my 90‑day accountability program), but I’m not dismissing your model because you’re not winning yet.