Recruitment automation isn’t a destination. It’s a decision - one that must be made at every step of the hiring process.
The rule is simple: where does a human add real value, and where doesn’t one need to be?
This article walks through the full recruitment journey, from job description to candidate feedback, mapping out where automation makes sense, and where it still doesn’t. Not in theory but in practice.
1. Job Description
This is where everything starts. Writing a great job description still requires context and nuance - but AI can help you get there faster.
Using LLMs, you can draft descriptions based on the role, stack, and company setup. Just don’t copy-paste - adapt the language to reflect your company’s tone and culture.
And if you’re looking to go beyond generative AI, tools like Datapeople help optimize job descriptions with real-world data — improving clarity, diversity, and candidate engagement before the post even goes live.
Automation level: Partial – draft + optimization
Tools: ChatGPT, DeepSeek, Gemini, Datapeople
2. Job Posting
Distributing jobs across platforms manually is a waste of time. Automate it. Some ATSs allow multichannel posting and A/B testing of job ads.
You can also generate adapted versions of the same ad using AI to better target niche channels.
Automation level: High
Tools: Greenhouse, Ashby, Teamtailor
3. CV Screening
Filtering hundreds of candidates to find the right ones is not where recruiters bring the most value. Let automation do the first cut.
Many ATSs now score CVs automatically, and LLMs can help with summarizing long profiles and matching them against role requirements.
That said, not all ATSs are equally reliable when it comes to parsing and filtering. Before placing full trust in automated scoring, it’s important to calibrate your ATS properly — test the filters, iterate, and refine them until you reach a level of confidence you can trust.
Automation level: High
Tools: Ashby, Lever, ChatGPT
4. Sourcing
Sourcing is about finding the right people - especially those who aren’t actively applying.
LinkedIn remains the most used platform for sourcing tech talent and where most candidates keep their profiles up to date.
For deeper sourcing, hireEZ and SeekOut go further by surfacing passive candidates across platforms (GitHub, Stack Overflow, personal sites), enriching profiles, and ranking results based on intent or skills.
Next-level tools like HeroHunt.io or Juicebox (PeopleGPT) allow recruiters to use natural language prompts to describe ideal candidates — even entering prompts like: “Find a mid-level Java Developer, working in a software house, with 5 years of experience, based in Portugal.” These tools then search across public profiles, resume databases, and open-source contributions to return matched candidates.
These tools give you more reach, better targeting, and often higher reply rates - especially when combined with a strong first-touch strategy.
Automation level: Supportive - expands reach, but human insight still drives targeting
Tools: LinkedIn Recruiter, hireEZ, SeekOut, HeroHunt.io, Juicebox (PeopleGPT)
5. Outreach: First Contact
This is where automation shouldn't happen.
That first message to a candidate should be written by a human - tailored, relevant, and honest.
Follow-ups? That’s where automation earns its spot - especially when done across multiple channels.
Automation level:
- First message: Manual
- Follow-ups: Automated
6. Interview Scheduling
This part should already be fully automated.
Let candidates choose time slots, sync with calendars, and integrate directly with your ATS.
Automation level: Full
7. Recruiter Interviews
Here, the recruiter’s job is to listen and ask suitable questions - not to take notes.
Tools like Krisp record, transcribe and summarize conversations. There are even more recruitment-focused options that can analyze sentiment or extract structured feedback.
A task that used to take 20 minutes now takes 5. You only need to copy and paste for records and read the summary to spot anything critical that might have been missed.
To make it perfect? Integrate the output directly into your ATS — so everything from summaries to candidate notes flows into your pipeline with zero extra steps.
Automation level: High (for note-taking and transcriptions)
Tools: Krisp, Metaview, HireLogic
8. Technical Interviews
When possible, technical interviews should be handled by engineers. But for screening or high-volume pipelines, automation can play a role.
Technical interview platforms offer live or asynchronous assessments with built-in scoring.
Automation level: Partial
Tools: CoderPad, Codility, Karat, ChatGPT (prep)
9. Feedback Loop with Hiring Managers
One of the main blockers in recruitment is feedback. The longer it takes, the more good candidates are lost.
Most ATSs now include Kanban boards for easy tracking, commenting, and handoffs. Structured forms, Slack integrations, and even AI-generated summaries can speed things up.
Automation level: High
Tools: Ashby, Greenhouse, Lever, Workable, Make, Zapier, ChatGPT
10. Candidate Feedback
Sending feedback emails is one of those tasks that are too important to skip — and too repetitive not to automate.
If your team records structured feedback during interviews, you can use AI to turn those notes into thoughtful responses. Automate the rest.
Automation level: High
Tools: ChatGPT, Make, Zapier
11. Follow-Ups & Database Updates (Voice Automation)
For companies with large candidate pools — like consultancies or high-growth teams — it makes sense to regularly check in with talent in your system.
Voice automation tools like GetVocal.ai allow you to do this at scale, validating availability, interest, and data quality.
That said, this type of automation should be used with care. It works best when candidates are already in your system and there’s a history of contact. The moment a signal of interest emerges, a human should take over the contact with the candidate. No automation replaces a real conversation.
Automation level: High, in re-engagement scenarios — but should always hand off to a human when interest is detected
Tools: GetVocal.ai, Voiceflow
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