AI and your resume: How to beat the bots

AI and your resume: How to beat the bots

Before you can interview for a new job, you must get past the AI tools that screen candidates. Experts share seven do's and don'ts for AI-proofing your resume

up
31 readers like this
ai fears

Nearly all Fortune 500 companies – more than 98 percent – plus an increasing number of smaller businesses filter resumes using an applicant tracking system before they ever make it to a human hiring manager, according to a 2018 analysis of job listings by resume optimization service Jobscan. “And it’s only a matter of time before AI-enabled tools become even more prevalent,” says Lisa Rangel, former recruiter and managing director of Chameleon Resumes. “Many larger companies are already using AI-candidate screening tools that focus on the whole candidate and not just a resume. As these tools become more mainstream and affordable, they will become more widely used.”

AI is infiltrating many processes related to recruiting and hiring, according to Al Smith, CTO with talent acquisition software provider iCIMS. “This includes screening candidate resumes in comparison to job descriptions and using AI-powered chatbots to streamline communications and schedule interviews,” Smith says. “Organizations are recognizing that machines can be incredibly efficient in identifying the most qualified individuals in the candidate pool, thereby giving recruiters the chance to focus their time on more meaningful tasks and building relationships with best-fit candidates.”

[ What artificial intelligence can and cant do now: AI in the enterprise: 8 myths, debunked. ]

But what does that mean for the candidate on the other side of these machine-driven hiring efforts? IT leaders can take steps to make sure their resumes are optimized to use this AI screening to their advantage – and avoid some common mistakes. Consider these do’s and don’ts:

1. Do spell out acronyms

This is true, both figuratively and literally. “Candidates should highlight all their skills that are relevant to a particular role on their application or resume,” says Smith. “Applicant tracking systems match keywords from job descriptions with resumes to find candidates that are the best fit for the role. Many AI tools also have semantic and synonym capabilities, so they can align similar language between job descriptions and resumes.”

Include any special projects, skill sets, and certifications, and the full name of relevant systems and software. It’s important to be accurate, Smith says, and define acronyms to avoid being filtered out of the pool.

[ Need updated advice on resume do’s and don’ts? Read also: Job hunt: 10 common resume questions, answered. ]

2. Don’t try to game the system

“It is incredibly important to be honest,” Smith says. “Some candidates apply to several jobs at an organization with a slight change to their email address or name. Applicant tracking systems are designed to match similar profiles, so the technology will catch and flag this, potentially reflecting badly on the submitted resume and impacting the candidate’s potential.”

Smith has seen some job hunters overload their resumes with keywords they think will get them in the door or sneak some in a white font readable only by machine. “While one may have the ability to trick an AI system to a certain degree, eventually a phone screening or live meeting with a hiring manager will bring to light that the applicant may not be as qualified as they claim.” 

3. Do differentiate yourself

Many job seekers assume that 100 percent compliance [with] the perfect keywords will get them past the screens, says Rangel. That’s not the case. Instead, candidates should focus on their achievements and differentiators in their resumes. In fact, Smith says, “they should avoid overloading their resume with the exact keywords from the job description, as advanced applicant tracking systems can recognize this and it may have potential to reflect poorly on the application.”

You may want to rethink overused words like innovation or transformation as well.

You may want to rethink overused words like innovation or transformation as well, advises Pat Ryan, executive vice president of enterprise architecture at SPR. “If a company is sifting through a collection of documents it will likely filter out words used by many people or that are filler words. If everyone wrote the words ‘innovative’ or ‘leadership’, then the algorithm might filter those words out, even if these words are individually important to the text being analyzed.”

4. Don't limit your job hunting to online submissions

“Realize that if you want a human to reach out to you, reach out to a human,” says Rangel. “Use the job posting to research the job.” Do some research using LinkedIn to get close to the hiring manager, and contact him or her directly or through a connection.

5. Do continue to network with human beings

“Networking [employee referrals, social media connections, and personal contacts] is still the best way to land quality jobs,” says Rangel. “There will always be a new tool or application that can make the job landing process smoother for some. Try it, but if the new shiny hiring tool doesn’t seem to work for you, know there is nothing wrong with you, but instead you might need to use a more traditional tactic that has been tried and true for years.”

6. Don’t wait for an opening to enter the resume tracking system

“Candidates should join talent pools for companies of interest, even if there isn’t a current role open,” says Smith. “When a relevant role opens, those in the talent pool will be among the first to know and could give them a competitive edge. “

7. Do consider the upside of AI in job hunting

While bot-enabled recruiting is new and imperfect, it has potential benefits not just for the hiring companies, but for IT leaders trying to land their next job. “AI can help eliminate human error by always ensuring that employers see the resumes of those who are truly qualified for the role,” Smith points out. “Without AI, a recruiter may miss a qualified candidate’s resume by simple mistake, or their own bias may get in the way of advancing a candidate to the next stage. AI screening systems also make it much easier for qualified candidates to be elevated for hiring manager review more quickly, as those who are not qualified are weeded out earlier the process.”

[ Read also: AI vs. machine learning: What’s the difference? ]

Stephanie Overby is an award-winning reporter and editor with more than twenty years of professional journalism experience. For the last decade, her work has focused on the intersection of business and technology. She lives in Boston, Mass.

7 New CIO Rules of Road

CIOs: We welcome you to join the conversation

Related Topics

Submitted By Ganes Kesari
October 18, 2019

Many analytics projects pass a pilot test with flying colors but fail to earn wide adoption. Here are five common culprits that doom projects – and advice for tackling them.

Submitted By Peter Phillip
October 18, 2019

With many digital projects, achieving a strong ROI means establishing a range to shoot for — while watching the intangibles.  Focus on engagement and experience.

Submitted By Kevin Casey
October 17, 2019

How does robotic process automation software handle repetitive tasks? Does RPA require coding? Where does it fit? Let’s break it down in plain terms

x

Email Capture

Keep up with the latest thoughts, strategies, and insights from CIOs & IT leaders.