AI Is Never Allowed Near the Price

A customer emails a wholesale distributor asking for fourteen things. Somebody opens the email, finds each item in the catalog, checks who can supply it and at what price, types the whole list into a quote, and sends it back. On an ordinary day that's a day or two of turnaround for an order worth maybe $1,200. The customer buys from whoever answers first.

Someone spent the last several months building an AI tool to do that job for wholesale distributors, then posted on r/ERP asking people who live in this work for a sanity check. The part you'd expect to be hard, reading the email and matching products, turned out to be mostly solved. The hard parts were somewhere else.

I read the post and the replies under it. Two things stood out, and both apply well beyond quoting. If anyone is pitching you AI for your order desk, your billing, or your inventory, they're what I'd want you carrying into that meeting.

The first came from the post itself. The builder set one rule without qualification: AI is never allowed near a price. Prices come from the catalog, full stop. The reasoning was blunt. Ask a model for a number often enough and eventually it will quote someone a made-up one, and you'll have to honor it.

I like this rule a lot, and not because it's cautious. It's specific. It doesn't say "be careful with AI," which is a sentiment. It names the one step where a wrong answer stops being a mistake and becomes a commitment, and it walls that step off completely.

The rest of the post shows why that kind of line matters. Wrong answers in this kind of system rarely announce themselves. A line like "Needed on site Thursday if possible" gets sent to the catalog and comes back "not stocked." A correction like "Sorry, make the pipe insulation 4 boxes not 2" gets treated as an unmatched item, the customer's change disappears, and you ship half of what they asked for.

The most expensive miss wasn't even the AI. Reading orders customers sent electronically, nine lines arrived with no quantity, and ordinary code filled in a 1 for each. Every line showed a green check, and $967 fell off the total. The quote looked exactly like a correct quote, because a wrong quote often does. The fix was to make it stop: a missing quantity now comes back blank and holds the whole document. As the builder put it, "a parser that half-works is worse than one that fails."

The steps that matter most in your business deserve the same kind of rule. When the answer has to be right, the system looks it up or it stops. It never fills in something plausible and keeps going. Before you adopt an AI tool anywhere in your order-to-cash process, walk each step and ask: if this went wrong silently, who would notice, and when? The steps where the answer is nobody, at least not until the margin is gone, are your do-not-touch list. Write it down before the demo, not after.

The second thing came from the replies. Right now, 46% of lines in the builder's system still get flagged for a human, against a target of 15 to 20% for genuinely useful. The post says so plainly rather than dressing the number up.

One reply pushed on that number in a way every owner should. Line-level accuracy isn't what decides whether anything changes on your order desk. What decides it is how many quotes a person still has to open. Take a fourteen-line quote at the 20% target, with flags landing at random, and someone still ends up touching roughly 96 quotes out of 100. Even at 15%, it's about 90. At today's 46%, it's effectively all of them. The work per quote shrinks. The number of quotes that need a human barely moves.

That gap is where AI business cases fall apart. An accuracy figure measured in lines can keep improving while your order desk stays exactly as busy. You pay people by the unit that lands on their desk: the quote, the order, the invoice. When someone shows you an accuracy number, ask what it's counting, and if it isn't that unit, ask them to convert it.

Both of these come back to the same trap. In each case, the display looked fine. Green checks on a total that was $967 short. A line accuracy number that can improve for months while nearly every quote still needs a person. Neither problem shows up in a demo, because a demo runs on clean emails with clear quantities.

Decide your do-not-touch steps and the number you'll judge the tool by before anyone shows you anything.

Then watch what happens in the demo when you tell the vendor.