The 3 Biggest Breakthroughs AI is Making in Sourcing

By Chris Murdock

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AI is making a big impact in the talent acquisition industry as we continue to diversify the candidate field. 38% of companies reusing AI and 62% expect to do so by the end of the year. Companies who use AI, predictive analytics and other technology tools show 18% higher revenue and 30% greater profitability compared to the companies who don't use a tool. AI is flipping the talent acquisition game from streamlining recruiting tasks to collecting relevant metrics and data to use in hiring.

Here are 3 of the biggest breakthroughs AI is making in the talent acquisition landscape:

AI creates an accurate picture of talent pools

75% of employers say they’re experiencing serious talent shortages. One of the major issues plaguing talent acquisition is the misconception that open jobs draw in qualified candidates. Just because you have a job opening doesn’t mean the right talent will just waltz through your door for an interview.

Because of this, many companies struggle to accurately identify what their talent pool is or even how big it is. Additionally, companies set unrealistic or false expectations for their open positions and end up restricting their net for qualified candidates. As a result, those open positions go months, maybe even years, unfilled.

AI resolves these issues with search algorithms to help identify potential candidates, especially for hard-to-fill jobs like engineering or tech development. The key concept here is that AI changes hiring from a reactive to a proactive process. Instead of waiting for those dreamboat rockstar employees to come to you, AI finds them first. AI tools like Karen.ai use candidate ranking to sort the list of the top talent and selects candidates that might be the best fit based on their experience, personality and other relevant, quantifiable data their algorithms find. It helps firms automate sourcing to find quality candidates in external databases or their own ATS.

Because AI focuses on the qualifications of candidates based on skills, experience and other work-related factors, AI eliminates bias. Sourcing talent based solely on their qualifications helps create diverse and dynamic teams.

AI improves job descriptions

A huge hurdle in the talent acquisition industry is attracting more diverse talent, and AI simplifies this by breaking down and analyzing job descriptions to help employers write better ones. Candidates hate complex job postings and confusing requirements sections. 60% of job seekers quit in the middle of filling out online job applications because of their length or complexity.

AI tools like Textio use writing enhancement powered by proprietary data sets of more than 350 million job posts to provide suggestions and language adjustments to help businesses expand their talent pools. It uses AI to analyze job positions in real time and gives employers recommendations to best fit a larger, more qualified talent pool. On top of predicting how candidates will respond to job posting content, it also eliminates bias by picking up on words or phrases that could come across as favoring masculine or feminine candidates.

AI algorithms can create a multitude of scenarios with each applicant — plugging in their skills and experience to see if they might be a good fit for the position. The algorithms then use the results to provide employers with different options for better, more well-suited job positions. What makes this breakthrough so fascinating is that the algorithms can be programmed to continuously update and learn, enabling them to search for new candidates that best fit the new job position.

AI sources passive candidates

As of May 2018, the U.S. currently has a 3.8% unemployment rate, but now 63% of recruiters are not finding enough suitable candidates to fill positions. It’s great that the U.S. is at the lowest unemployment rate since before the Recession, but now the problem is finding available, quality talent to fill open positions for vacancies and expansions.

The solution to the lack of available talent? Source passive candidates — or candidates that are already employed, but would be open to other opportunities depending on the offer. 71% of adults already in or looking to enter the labor force say they are actively looking for or open to a new job, and 73% agree it’s important to be aware of jobs that are currently out there. Continuing on this idea, 42% of employees say they’re not actively looking yet are open to considering a new position. Passive candidates are out there, it’s reaching them that is the real challenge.

That’s where AI comes in. AI and machine learning algorithms help find candidates through predictive labor metrics like how long candidates usually stay in a given job and environmental influences like whether their company is downsizing. These candidates can then be filtered by job criteria to find the best candidate that fits the open position. In other words, AI brings businesses and passive candidates together faster by eliminating the need for ad hoc searches.

AI cuts out the menial recruiting tasks that create complicated sourcing processes all while learning how to consistently improve the way we source talent. Could this all be the beginning of self-aware technology? Will we soon have intelligent, robotic recruiters completely sourcing our talent for us? Who knows, but what we do know is that it simplifies and improves upon numerous talent acquisition dilemmas.

Technology isn’t the only way to help bolster your recruitment process. Thinking about scaling your company, but your recruitment team doesn’t have the bandwidth to do so? Take this quiz to see if your team is ready for a sourcing partner.

About Chris Murdock:

Chris Murdock is the Co-Founder and Senior Partner of IQTalent Partners. Chris has over 12 years of executive recruiting experience and leads search execution and client relationships along with supporting searches across the firm. Prior to Founding IQTalent Partners, Chris was a sourcer with Yahoo!’s internal Executive Recruiting team in the corporate offices in Sunnyvale, California. Previous to Yahoo!, Chris was an Associate in the Menlo Park, California office of with Heidrick & Struggles, where he recruited for software, hardware, professional services, and semiconductor clients. Before Heidrick & Struggles, Chris worked in the Retail Practice of TMP Worldwide in Atlanta, Georgia. While with TMP Worldwide, he worked on CEO, General Merchandise Manager, and various VP and Buyer level searches. Chris earned a bachelor’s degree from Vanderbilt University.

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