3 Major Benefits That Recruiters Enjoy By Using AI In Sourcing

Sourcing – finding and qualifying candidates who have not applied directly to an open role – is the second best hiring source, accounting for up to 33% of hires.

ai for sourcing

Korn Ferry’s latest survey found 69% of talent acquisition professionals  believe using AI as a sourcing tool has resulted in higher quality candidates.

Clearly, recruiters that leverage technology like AI for candidate sourcing have an advantage in today’s tough talent market.

Here are the 3 major benefits recruiters are enjoying by using AI in sourcing.

Benefit #1: Freeing up recruiters’ time

According to Korn Ferry, recruiters are seeing the value of using AI in sourcing:

  • 48% state AI is making their job easier
  • 40% believe AI provides valuable insights
  • 27% say AI has freed up their time 

Entelo’s data shows the average talent acquisition professional spends about 1/3 of their work week sourcing candidates for a single role, which is around 13 hours a week. In terms of recruiting KPIs, AI for sourcing candidates improves efficiency metrics such as time to fill and cost to hire.

In terms of recruiter time, Laurie Padua of Alexander Mann Solutions believes using technology like AI to automate sourcing can free up three to five hours per day, an increase in recruiting efficiency of nearly 40%.

Benefit #2: Finding higher quality candidates

AI can help you find higher quality candidates by increasing the accuracy of candidate matching.

Instead of using error-prone keyword and boolean searches, AI finds patterns in resumes and other data sources to find candidates that are better matches for a job’s requirements. This can involve general searches for candidates by scraping the web or specific searches within resume databases such as CareerBuilder.

Another big trend in candidate sourcing right now is rediscovery: re-engaging prior candidates.

Candidate rediscovery uses artificial intelligence to source candidates by shortlisting and grading qualified candidates (e.g., from A to D) who’ve applied to a previous role by screening their resumes in your ATS.

Benefit #3: Reducing unconscious bias during sourcing

Research has found that unconscious bias exists at the sourcing stage: resumes with English-sounding names receive requests for interviews 40% more often than identical resumes with Chinese, Indian, or Pakistani names.

AI technology has the potential to reduce bias at the sourcing stage by ignoring candidate demographics (e.g., race, gender, age) in its decision making.

Because AI can be used to create a profile based on the qualifications of successful employees, a major advantage AI has over humans is that its results can be tested and validated.

Recruiting AI software can be tested for bias by using it to source and grade candidates, and then assessing the demographic breakdown of those candidates. This type of human oversight is still necessary to ensure the AI isn’t replicating existing biases or introducing new ones based on the data we provide it.

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Ji-A Min

Ji-A Min

Head Data Scientist at Ideal
Ji-A Min is the Head Data Scientist at Ideal. With a Master’s in Industrial-Organizational Psychology, Ji-A promotes best practices in data-based recruitment. She writes about research and trends in talent acquisition, recruitment tech, and people analytics.
Ji-A Min

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