Companies have been using some form of automated resume screening for a long time, so the idea of AI resume scanners isn’t exactly new. Nor is it just about hiring managers being too lazy to do it themselves. Sometimes the number of resumes is just too overwhelming (many hundreds) to manually eyeball the scan. I get that.
But here’s the problem: one of the best candidates I ever hired would never have made it through an automated scan of any kind. And yet she was ideal for the job. What gave me the advantage was that I personally screened all the resumes (there were only about 40) and I spotted the non-linear reasons she might fit our needs well.
What do AI resume scanners want?
First, whatever the level of automation, a human has to program the criteria. And it’s not always a person who knows the actual work on a first-hand basis. In many companies, a Human Resources staff member has that honor, hopefully with input from the department hiring.
They make their best guess based on the job description which is filled with a variety of keywords and phrases that they select. Of course, someone also wrote the job description and hopefully that also includes input from the department that the position is in.
But even with a well-written description, the screening criteria don’t always capture some of the less tangible elements that might make a candidate a great fit for the job. The kind of thing a good read-through of a resume and cover letter can do far better. And more and more is lost in the automation shuffle.
Still, whoever or whatever is screening your resume — even AI resume scanners — you, the job seeker, want to make sure you emphasize experiences that include keywords and phrases from the description. And make sure at least some of them are in your Qualifications Summary / Professional Summary section at the top. (Forget the outdated Objective, ok?)
⇒ Resume Tips: Match Your Resume to the Job!
A compromise AI resume screen method?
So we’ve established that sometimes strictly human initial screening may not feel practical — especially if the company gets 500+ resumes for a single posting. And maybe they have more than one job opening at the same time. And maybe they are understaffed. which is why they’re hiring. Screening takes time when it’s done the old-fashioned way.
Yet purely automated screening with only a few resumes selected to pass on to the department can eliminate some great candidates. I’m guessing many of you have had that happen at one time or another. And it’s an unfortunate loss of talent for companies that would benefit from more than just cookie-cutter employees. Sometimes the “outlier” is just what’s needed to solve problems and create new ways of doing things.
So what can companies do to maximize the chances of success from a costly (time and money) hiring process? They can decide that hiring great employees is worth some extra time and effort. Not that they need a person to read each and every resume (some are easily discarded).
But what if they were to widen the initial scan criteria they use (number of years, specific combinations of required skills, education, etc.) and then eyeball a larger number of semi-finalists? Some compromise between too strict and too useless might help solve the problem.
Even a brief personal perusal (I’ve done it many times) can quickly spot the “not even close” resumes. But you can also find some interesting outliers worth reviewing more closely. And you’d still get the ones who would have been selected by AI resume scanners or any automated process.
The thing about describing the perfect new hire
is sometimes you don’t know who they are
until you find them!
More posts to help
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12 Things You Need To Know BEFORE a Job Interview
18 Practical Tips to Help You Ace Your Job Interview
What Is a Targeted Resume or Cover Letter?
Cover Letter Basics: What Goes Into a Strong Cover Letter?
Start Building Networking Connections That Last
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