How to Use AI in Recruitment: What Actually Works, Stage by Stage

What’s the use of speed if you’re heading in the wrong direction?

As AI takes the world of recruitment by storm, we should consider this: 89% of HR professionals say AI saves time in recruitment, but only 24% say it has improved their ability to identify top candidates and overall hiring quality. Most of the organizations that speed up the recruitment process with AI seem to be struggling where it matters. 

That’s because AI in recruitment that merely automates activity differs from AI that improves hiring decisions. 

Between the two, only AI that creates better quality of hire gives organizations the best bang for their buck. Companies that focus on automating recruiting activities end up making bad hires faster and at scale.

In each stage of the recruiting funnel, AI can either be used solely to speed things up or produce genuine improvement in hiring quality with strategic acceleration. This article details how to use AI in recruitment and points HR leaders to what they should be demanding from the tools they adopt at each stage.               

AI in recruitment stage 1: Sourcing 

Automating recruiter activities at the early stage of recruitment makes the workload lighter. Countless professional networks can be searched, and candidates who match keywords can be identified within minutes. Outreach messages can be crafted and sent to thousands in an instant.

Though productive, this doesn’t always translate to better hiring quality because if the tool is trained to source candidates on proxies, it might miss potential candidates who have the necessary skills for the job.   

AI tools improve hiring quality at the sourcing stage when they’re designed to look for evidence of skills associated with success in the role. The focus on demonstrated competencies and transferable skills, relevant experience, learning agility, and skills acquired through nontraditional career paths grants access to a larger and better talent pool. 

When sourcing for candidates, HR leaders should look for tools that prioritize skills and job-relevant evidence over superficial credentials.    

AI in recruitment stage 2: Candidate screening

Candidate screening is a popular use case of AI in recruitment.   

Companies often automate the process to identify keywords and extract qualifications from resumes, identify apparent skills, rank applicants, and eliminate or move candidates through the ATS. Sure, this turns hours of manual resume review into minutes. But it only reflects the organization’s decision model, which might just be flawed.  

Rightly implementing AI in the screening stage can strengthen organizations’ hiring decisions. 

AI platforms can predict job and culture fit by working with data. For example, Jules AI uses predictive analytics to determine whether the evidence available about each candidate correlates with success in that role. Tools that are trained on fairness and broad datasets eliminate bias from resume ranking, allowing qualified candidates to be identified regardless of their profile, which makes for better hiring outcomes.  

When picking an AI tool for candidate screening, pay attention to the candidate characteristics each platform considers and whether they have any predictive value. Look out for responsible design and oversight features.        

AI in recruitment stage 3: Assessments

The difference between automation and AI that drives real improvement in hiring decisions shines in the assessment stage. That’s because candidate assessment is aimed at predicting who will actually succeed in the role. 

Mere automation smooths test administration, answer evaluation, and grading. It’s quick but offers little insight into job relevance because the focus might be on shallow metrics such as familiarity with the assessment format, speed, and high test scores.  

Better use of AI prioritises using job simulations, situational judgment tests and communication exercises to identify patterns. Recruiting professionals can gather more reliable evidence of future performance through different tests that gauge both hard and soft skills. This will help organizations determine each candidate’s job and culture fit. 

With Jules, you can generate assessments tailored to the requirements detailed in your job description. It can also simulate scenario-based situations to check how well candidates can apply their skills in context.

Your AI tool for candidate assessment should track candidate abilities closely tied to job success.       

AI in recruitment stage 4: Interviewing 

More than 59% of companies that implement AI in interviews use it for transcription, body language assessment, facial recognition data collection, and candidate language analysis. Question generation and keyword identification are some other functions of automation. 

But they don’t mean that the candidate is thoroughly evaluated. 

Proper use of AI supports the interviewer’s judgment. When AI is used to map questions to predefined abilities, design similar questions, evaluate the same criteria, and prevent unconscious bias, the interviewing process yields better results. Every decision needs to be backed by evidence and candidate communication skills gauged effectively. This will allow the most competent candidates to shine. 

Jules tailors interview questions to the role. Its asynchronous video interview scoring functionality ensures candidates’ answers are evaluated against relevant job criteria. 

HR leaders should ensure the AI platform they use for interviews can eliminate subjectivity. The tool’s decisions should also be explainable and support recruiter oversight.       

AI in recruitment stage 5: Scheduling

Automation can make scheduling easier by coordinating the calendars of multiple interviewers to find mutually available times, accounting for time zone differences, setting interview times, and sending reminders.

This doesn’t move the needle as far as improving the quality of hire is concerned. But if AI is implemented during scheduling to reduce delays between interview stages, minimise scheduling delays, and prevent interview fatigue, it will prevent top-candidate drop-off. Quality candidates don’t last long on the market. 

Jules connects interview scheduling with the actual interview process. It offers self-scheduling for candidates, real availability across panels, recruiter control, calendar integration, and personal panel notes, all of which ensure top-candidate engagement. 

AI in scheduling should actively support better hiring decisions by being connected to the interview process and tracking vital metrics like time-to-interview, time-to-decision, interview completion, process consistency, and candidate experience.   

AI in recruitment stage 6: Reference checking

During reference checking, HR leaders should prioritise extracting predictive evidence instead of checking references as a formality.

Automation in reference checking can include contacting references, sending questionnaires, collecting responses, and summarising feedback. To improve hiring quality though, AI should be used to assess the reliability of the reference and spot any contradictions in the candidate’s claims. This will validate the claims of quality candidates, allowing them to progress in the recruiting pipeline, while flagging candidates whose claims are unverified.

With Jules, you can generate reference questions tailored to the job. For a sales role, it can create questions on the candidate’s ability to handle difficult customer negotiations and manage pipeline performance. Structured response scores are combined with the real context behind the reference’s answers to give detailed information. 

Fraud protection is also in place to protect potential employers from fabricated references or misleading reference information.  

Your reference-checking AI tool should go beyond verifying employment dates to collect insights critical to success in that role. It should also focus on catching fake references and claims. 

HR leaders who understand how to use AI in recruitment will notice an improvement in hiring decisions. What’s more, they won’t miss out on faster recruiting. If you’re ready to improve your hiring, reach out for a demo today.