Artificial Intelligence in Recruitment

Artificial intelligence in recruitment

This article is about the application of Artificial Intelligence in Recruitment. 

Recruiters increasingly use AI. For example to make the first round of cuts, and to determine whether a job posting is advertised to certain candidates. These applications learn from data that has been collected from the previous candidates. So recruiters can cut down on the effort to fill a position. Last year, 67% of all the hiring managers and recruiters surveyed by LinkedIn, said that AI-applications saved them time. And you should work with AI too. That’s why this great article, written by Rebecca Heilweil for

Recruiters using Artificial Intelligence

In recruitment, you can use artificial intelligence throughout the hiring process. From advertising and attracting potential applicants to predicting candidates’ job performance. Another use of AI is screening application materials, like résumés and assessments. The AI-application then recommends which candidates recruiters should contact first. But AI doesn’t just operate behind the scenes. You can even use Artificial Intelligence in the pre-screening phase of your recruitment process. So, help yourself and use a chatbot!

These tools help recruiters to move quickly through large pools of applicants and makes it cheaper to attract great candidates. Proponents say they can be fairer and more thorough than overworked human recruiters. If you have time because of great Artificial Intelligence tools, skimming through hundreds of résumés and cover letters would be a piece of cake right! Because these tools are able to recognize traits in the resumes, and they can see from previous successful hires, what works for your company and what isn’t.

Hire faster and cheaper with AI

“Companies just can’t get through the applications. And if they do, they’re spending — on average — three seconds per application,” Somen Mondal says. “There’s a whole problem with efficiency.” He argues that using an AI system can ensure that every résumé, at the very least, is screened. So you don’t miss out on great candidates! After all, one job posting might attract thousands of applications, with a huge share from people who are completely unqualified for a role. Such tools can automatically recognize traits in the application materials from previous successful hires and look for signs of that trait among materials submitted by new applicants. Mondal says systems like Ideal can consider between 16 and 25 factors (or elements) in each application, pointing out that, unlike humans, it can calculate something like commute distance in “milliseconds.”

“You can start to fine-tune the system. So you’ll end up with not just the people you’ve brought in to interview, or not just the people that you’ve hired. You’ll get people who ended up doing well in the position. So it’s a complete loop,” Mondal explains. “As a human, it’s very difficult to look at all that data across the lifecycle of an applicant. And with AI this is being done in seconds.”

These AI systems are only as good as the data they’re trained on and the people who have built them. If developers train a résumé-screening machine with historical data, the system will inherit both the conscious and unconscious preferences of the hiring managers who made those selections. An approach that could help find stellar, highly qualified candidates.

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