# Recruitment firm: from 22 hours of CV screening to 4

Source: https://getstartedwithai.net/case-studies/recruitment-firm-22-hours-to-4
Site: Get Started With AI
Tagline: Build AI automations that actually run your business.
Audience: solo professionals, freelancers, consultants and AI implementers in training
Contact: hello@getstartedwithai.co.uk

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# Recruitment firm: from 22 hours of CV screening to 4

A 15-person recruitment firm spent 22 hours a week on candidate screening: reading CVs, copying data into the ATS, sending the same three rejection emails. They had tried two AI tools in the prior 12 months and both failed. The diagnosis on the previous failures was the same in both cases: tool-first, process-blind. The WIRE Method audit named a different fix.

## The starting point

- Hours per week on screening: 22, split across three recruiters.
- Previous AI attempts: two failed deployments in 12 months.
- Tooling at start: an ATS, an email client, a spreadsheet for tracking.
- Stated belief: "AI is not ready for recruitment work."

## What the audit revealed

Both failed attempts had skipped the W and I steps of the WIRE Method. They had picked tools first, then tried to make the process fit. The work was not documented, the data was not consistent, and no single person owned the workflow end to end. The fix was to start with the process, not the tool.

## The first automation we built

- Step W: mapped the screening process minute by minute. Three recruiters, three slightly different versions.
- Step I: picked CV intake classification as the first build. Highest hours, simplest decision tree.
- Step R: built the automation in two days using Zapier, a Make scenario and one ChatGPT prompt.
- Step E: named one recruiter as the owner. Set a weekly 15-minute review of flagged edge cases.

## The result

- Hours per week on screening: 4 (down from 22).
- Saving: 18 hours a week, equivalent to roughly £40,000 of recruiter time annually.
- Tool cost: £77 a month total. No developer involved.
- Time to first working build: 4 working days from kickoff.
- Stable for 11 months at time of writing, no significant rebuild needed.

## What we did not automate first

Interview scheduling was the biggest hours category but the wrong first build. It involved candidates, hiring managers, internal calendars and at least four exception types. Scheduling went into Phase 2 (six weeks of build) after CV screening had stabilised. Picking the readiest workflow, not the biggest, was the move that made the engagement work.

## See this kind of build run live

The free webinar walks through the WIRE Method end to end on a real audience workflow. 60 minutes, no upsell. Bring one repeatable task; leave with a mapped automation.

### Live build session

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## Questions people ask before they start

### How long until they saw the saving?

Week one. The automation went live on day four. By the end of week one the team had completed 30 percent more screening with 70 percent less time.

### Did the previous AI tools get scrapped?

Yes. Both subscriptions were cancelled. The replacement was simpler, cheaper and connected to a documented workflow.

### Was a developer involved?

No. Zapier, Make and ChatGPT did the wiring. The recruiter who owned the process is not technical; she runs the weekly review without help.

### Can this work for a smaller recruitment firm?

Yes. The pattern works at 5 staff and 50 staff. Smaller firms are usually faster to ship because the decision-making is direct.