How AI automation agencies find companies worth selling to.
An agency sells the absence of a solution. Your best customer is a company still doing by hand the thing you automate, and absences are harder to search for than tools. But they leave traces, mostly in job descriptions, and this page is about reading them. The long version of the method is in our post on finding clients for an AI automation agency; this is the prospecting profile.
Prospecting for AI automation agencies, the way we do it: infer your ideal customer profile from your own site, pull candidates from the sources where your buyers leave signals, screen them cheaply, then read each survivor’s pages against a fixed set of checks. You get 8–25 companies, ranked, with a quote and a URL behind every claim. Try it on find-customer for free.
What your ICP usually looks like
- How it's defined
- workflow-defined; strongest when you restate it as a role ('hiring for the job we automate') or a tool ('their job posts mention the spreadsheet we replace')
- Size band
- 50–1,000 employees; enough headcount in the function that automating it is worth a project fee
- Likely buyers
- Head of Operations · COO · Head of Support or Finance depending on the workflow · occasionally a CTO who owns 'AI'
How we infer it from your site
For agencies we weight case studies over the homepage, because agency homepages say 'we transform businesses with AI' and case studies say who paid and for what. We extract the workflow, the industry, the before-state ('dispatch on spreadsheets') and the buyer from each case study. If your case studies split into two audiences we infer two segments and ask you to pick one per run; blended agency ICPs match nobody.
Typical sellers on this profile: workflow automation builds, custom AI agents, RAG and internal search, back-office automation, AI implementation partners. You see the inferred fields before any research starts and can correct them.
Where your buyers leave signals
| Signal | Where we read it | What it proves |
|---|---|---|
| Manual-process language in job posts | Public ATS boards and careers pages, searched for 'spreadsheet', 'manual', 'phone and email', 'shared inbox' | A job description is a company describing its Tuesday; named absence of tooling is the best problem evidence an agency can get |
| Headcount in the function | Careers volume in ops, support, finance or back-office roles | Ten open support roles is a support org big enough to automate |
| Stated initiatives | Annual letters, 'our plans' posts, founder interviews | 'We aim to automate X this year' is a quote for the subject line |
| Tooling gaps | Legacy or fragmented tools named on the site or in job posts | 'Experience with our custom Access database' is a flare |
| No automation vendor | Absence of an automation platform on integration and careers pages | Tool presence flips sign for agencies; we make displace_competitors explicit rather than guessing |
Typical fit rate: 10–20% for a pain-defined ICP ('manual back-office'); 40–60% once restated as a role or tool. Sources whose membership already proves something beat generic search, which has a 5–10% prior; the reasoning is in how to build a target account list from your website.
Queries that find them
- site:boards.greenhouse.io "operations coordinator" "spreadsheet"
- "customer support" careers "shared inbox" "high volume"
- "our priorities for 2026" "automate" site:*.com
- "accounts payable" "manual" "invoices" careers
What problem evidence looks like
A check passes only with a quote from a page we fetched. For AI automation agencies, the lines that pass most often look like these:
- “Update customers on shipment status via phone and email, maintain our dispatch tracker in Excel”
- “Process 300+ invoices a week from PDF into our accounting system”
- “Wear many hats and help us build the process from scratch”
Default for this profile: no. For most agencies a company already on an automation platform means the itch is scratched. Default no. Flip it if your offer is replacing a failed automation vendor.
Disqualifiers we apply
- Companies with a dedicated automation or AI team (they'll build it)
- Other agencies (competitor)
- Sub-50 companies where the workflow is one person
- Already a client or a named case study (checked automatically)
What a qualified card looks like
Illustrative example, not a real company
Mid-size 3PL running dispatch and customer updates on manual processes, hiring three operations coordinators, and stating a 2026 goal to 'automate shipment status communication'.
- “Over 240 employees across 6 terminals” — /about
- 3 open Operations Coordinator roles — /careers
- “maintain our dispatch tracker in Excel” — /careers/ops-coordinator
- “automate shipment status communication in 2026” — /news/2026-plan
- Funding — Not found
Three ops roles posted this quarter
VP Operations
The score is arithmetic on check verdicts, not a model’s opinion; the weights are in our ICP scoring formula.
Questions AI agencies ask
- Our agency serves several industries. Can one run cover them all?
- No, and it shouldn't. We infer up to two segments from your case studies and ask you to pick one per run. A blended profile produces queries that match neither audience.
- Does it find companies that don't use any automation yet?
- It looks for the traces: manual-process language in job posts, headcount in the function, stated goals, legacy tooling. Absence of a vendor is one signal among those, never the only one.
- What's the difference between this page and the blog post on finding agency clients?
- The post is the full method with the reasoning. This page is the prospecting profile: what we read on your site, where your buyers leave evidence, and the checks we run.