Artificial Intelligence in Campus Recruitment

Can artificial intelligence assess a student’s resume the same way as an experienced campus recruiter? That was the question asked by a large energy company.

They receive thousands of applications to their graduate and intern programs for engineering, commercial and technology roles. Resumes were reviewed manually. The turnaround time to complete these reviews placed a considerable burden on key staff. Not only the time pressures and the need to fully and objectively assess each applicant. But coping with other day-to-day responsibilities. ?

The time had come to find a technology solution. Significantly streamline the review process while maintaining the integrity and validity of the assessment.

But any solution needed to be much more than applying filters. Their applicant tracking system already did that.

What they wanted was a way to assess the quality of their applicants.

After all, that’s what an experienced recruiter does. They consider all of the applicant’s resume data. From academic background and performance, to their work experiences and the roles they’ve held, through to extra-curricular activities and personal achievements. They look for indicators of key behavioral skills like leadership and initiative. Intrinsically, it’s an assessment of all of that information relative to the requirements of the role and likely fit with the company's career offering.

It was a big ask but if they could automate initial screening, the most time-consuming process, they could spend more time with their best applicants at interview stage.

They chose to evaluate GradSift. In simple terms, it's an assessment/shortlisting platform that replicates a manual resume review. Its algorithm interprets an applicant’s background just as an experienced recruiter does. Employers set selection criteria, effectively modifying the algorithm for each role. Applicant data is captured from selections from drop-down fields, with no key words or resume parsing.

As a first step, the talent acquisition team wanted assurance that GradSift’s algorithm would match their own assessments. They understood how it worked. But they wanted to be certain. Will it work for us?

They gave GradSift twenty blind resumes from their recent applicants. A mix of hires, some who were close and others knocked out early. GradSift processed the data. The talent acquisition team were given the ranked results.

Their conclusion? "We're impressed!" GradSift assessed their applicants the same way they had.

It had successfully interpreted applicant quality.

That gave them the confidence to go ahead.

For their next (and subsequent) programs they successfully used GradSift for initial screening. “It saved hours and hours of time in our recruitment processes. It streamlined our shortlisting process and gave more depth and consistency to the criteria we use to select candidates.”

A by-product has been greater diversity among hires. That’s a result of blind screening avoiding subconscious bias that can creep in with recruiters reviewing so many resumes.

Artificial intelligence, designed correctly, does work and can avoid bias. Many recruiters understandably still have doubts. But manual resume reviews come with their own downsides – enormous time and lost productivity, subconscious bias, risk of reduced diversity and the systems difficulty of going back to reconsider applicants.

Ten years into the future, how many employers will still be manually screening thousands of student resumes?

If you'd like to see if your company is ready for automated campus resume reviews go to: https://gradsift.com/solutions/put-gradsift-to-test/

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