Guide
AI Automation for 7- and 8-Figure Companies
Most companies between $3M and $10M have the same problem in a different costume. The owner is still in every decision, hiring has stopped helping, and three or four operations eat the entire week.
This page is the map of what AI actually removes at that size, what each operation is worth when it goes, and how to tell whether you are ready. Everything under it goes deeper on one piece.
The short version
AI automation is worth doing in a $3M to $10M company when a high-volume operation requires judgement, has years of history to learn from, and currently waits on a specific person. Quoting, support, dispatch, onboarding, and invoicing are where the money usually is.
The distinction that decides everything
Traditional automation runs a rule you wrote in advance. AI automation makes the decision the rule could not express, learned from work your company has already done.
That is not a technical distinction, it is a commercial one. The work that costs you money is almost never the moving of data. It is the two days a quote waits for judgement, the coordinator holding the dispatch board in their head, the three people answering the same forty questions.
If you can explain a task to a new hire in one sentence, buy a $40 tool. If explaining it requires the phrase it depends, that is the work worth replacing.
The five operations that carry the cost
Across the systems we have put live, the same shortlist comes back in a different order depending on the business.
| Operation | What it costs before | What it looked like after |
|---|---|---|
| Quoting | Two days per estimate, a fifth going stale | Two-day estimates going out in four hours |
| Customer support | Three people on inbox and chat | The system carries the load, first reply in minutes |
| Speed to lead | Four hours, overnight leads waiting until morning | Four minutes, close rate 19% to 28% |
| Onboarding | Three days of setup before delivery starts | Forty minutes, delivery starts the same week |
| Invoicing | Sent the week after the job closed | Sent the day the job is marked complete |
The full list of what has gone live, with the businesses behind each one, is on the transformations page.
How to tell whether an operation is worth replacing
Four tests. Work that passes all four is where the money is, and work that passes none should be left alone or handed to a connector.
- Frequency. It happens many times a week, done by several people.
- Judgement. Explaining it requires the phrase it depends.
- History. Your company has done it enough times to leave a record: quotes sent, replies written, jobs assigned.
- Cost of error. Getting it wrong costs money, which is why it currently waits for a person.
The fourth test is the one people skip. Work that waits for a person waits because someone decided a mistake was expensive. That waiting is the cost you are actually paying.
What the money actually goes on
Not the tool. Never the tool. In every project we have run, the cost sits in four places, and only one of them is building.
- Deciding what to build, which is why the assessment covers the whole company rather than the part you flagged
- Preparing your history, and resolving the places where written policy and actual practice disagree
- Testing against real historical cases where the correct answer is already known
- Training the person who will own it, until they run it without anyone in the room
Companies that skip the first build something impressive attached to a cost line that was not the problem. That is the single most common failure in this category and it has nothing to do with the technology.
Where AI automation is the wrong answer
Below about $3M it is usually a people or process problem, and a system built on top of a broken process fails faster and more consistently.
Above roughly $10M, somebody inside should already own this, and the money is better spent on that person than on us.
And if AI is going into what you sell, hire. You cannot outsource your product.
How to compare your options
There are five categories competing for this budget: connectors, agent platforms, assistants, agencies, and consultancies that build. Each one is genuinely good at something and useless at the others.
Pick by what you are missing rather than by feature list. Missing a rule between two apps is a connector problem. Missing time in one person's day is an assistant problem. Missing a decision about what is worth building is neither.
Questions
What size company is AI automation worth it for?
Roughly $3M to $10M in revenue, where the owner is still in every decision and hiring has stopped helping. Below that it is usually a people problem. Above it, someone inside should already own this.
How long before it is live?
Weeks. The assessment is measured in days, the build and data preparation are the bulk of the work, and training overlaps the end of the build rather than following it.
What do we need to have ready?
History of the work being done: past quotes, sent replies, job records, exports from whatever system holds them. It does not need to be tidy.
Do people lose their jobs?
In the companies we have worked with, people moved onto work a system cannot do. At this size there is usually more work than people.
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Related writing
Find out what your most expensive operation is
The assessment covers the whole company: how you get customers, how you deliver, and how the place runs. You get it in writing, and you can build from it with or without us.