Are you terrified you’re going to be replaced by a robot? This fear seems common these days, especially among recruiters. Many people working in talent acquisition are both curious about artificial intelligence (AI) – it ranked as one of the top global recruiting trends in a recent LinkedIn report – and worried about what it means for the future of their profession.

The concern is understandable. AI is an emerging field that is not well understood by the general population. However, I believe that AI is not here to replace recruiters. It’s here to make our lives easier, to automate tedious tasks, and to free up time so we can focus on things that really matter, like strategizing and building relationships with candidates.

In order to put some AI fears to rest, I’d like to look at three of the ways that recruiters can use AI to become more effective in their jobs:

1. Using AI to Write More Effective Job Descriptions

Writing a job post that attracts a diverse pool of qualified candidates requires more than a snappy company description and a rundown of job duties. In fact, your job ads could be unintentionally repelling the candidates you want, even if it looks like all the basics are there. Your descriptions could be too wordy, too jargon-y, too long, or even too short! Worse yet, you might be writing biased job posts without even realizing it.

How can you know if the language in your job posts is going to be effective and unbiased? Companies like Textio give you access to data crowdsourced from millions of job posts to predict the performance of your job post and help you improve it. Tools like these are nearly as easy to use as spell checkers, and the more posts they analyze, they smarter they get.

2. Using AI to Eliminate Scheduling Headaches

One of the most time-consuming and thankless tasks recruiters handle is scheduling interviews with candidates. The process generally takes multiple rounds of email – and hours of recruiters’ time – to finalize a date and time for an interview. All this back and forth introduces many opportunities for error. And don’t even get me started about what happens when someone has to cancel or reschedule!

This is why some of the latest scheduling AI tools like My Ally and GoodTime are so exciting. My Ally uses a virtual assistant, cc’d on your emails, to take care of scheduling, while GoodTime syncs information from calendars to find available times and make sure interviewers don’t get overbooked.

3. Using AI to Assess Candidates Efficiently and Objectively

In today’s market, recruiters are flooded with resumes, most of which come from unqualified applicants. There aren’t enough hours in the day to thoroughly assess each candidate, and unconscious bias can quietly guide even the most astute recruiters to choosing candidates for the wrong reasons.

Fortunately, resume screening is exactly the kind of tedious work with which AI can help. Moreover, since these AI recruiting solutions remove the element of subjectivity from the selection process, they can also reduce bias and help you build a diverse pool of talent. There are plenty of solutions available, like Pomato, which helps recruiters analyze candidates’ resumes, and HireVue, which integrates AI with video interviews.

While these point solutions can be quite helpful, other solutions fit AI into your current workflow. That’s the design philosophy behind Uncommon IQ, a qualification-based talent marketplace that sends streams of vetted candidates directly to recruiters’ applicant tracking systems or inboxes.

AI and the Future of Recruiting

AI doesn’t eliminate the need for recruiters. Rather, it allows recruiters to focus more on hiring great talent and less on tedious, low-value activities like digging through unqualified resumes. Hiring people is one of the most rewarding and beneficial parts of building a business, and I am genuinely excited about how AI can help us become more effective recruiters.

About the Author Teg Grenager

Teg is a data scientist, product manager, and serial entrepreneur who is the CEO of Uncommon, a platform that is revolutionizing the way that companies source talent. Uncommon came out of Beta and announced $18M in Series A funding in February 2018. Previously he cofounded and led product at, acquired by Aol in 2013 for $405M. Prior to, Teg was a Ph.D. candidate in Computer Science at Stanford University, studying machine learning and computational linguistics.

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