With Skilled Applicants in Short Supply, AI Emerges to Lure Passive Candidates

With unemployment down and skilled workers hard to find, artificial intelligence is proving itself an invaluable ally to hiring managers. A new report by ENGAGE Talent reveals how AI dives deeper into the talent pool.

May 16, 2018 – These are challenging days to find well-qualified talent for top roles. Beyond the well-documented, worldwide shortage of talent, unemployment is down. In fact, it hit a 19-year low of 3.9 percent in April, according to the latest Bureau of Labor Statistics (BLS). The unemployment rate for college-degreed workers who are 25 or older was just 2.1 percent. These are the professionals in the highest demand by employers.

Unemployment rates for some occupations are even lower. The unemployment rate for accountants and auditors, for example, was 1.9 percent in the first quarter of 2018, down from 3.1 percent from a year earlier, according to the BLS. The unemployment rate for financial managers was 0.5 percent and just 0.7 percent for financial analysts.

“All these trends in the market make recruiting and talent acquisition even harder,” this according to a new report by AI recruitment software company ENGAGE Talent. “Fewer and fewer candidates are looking for jobs; therefore it’s more difficult to find top talent. It’s even more important today to identify and engage top passive talent that aren’t putting their resumes on job boards.”

Job postings are the most common way to fill jobs but these postings are only hitting a fourth of one’s candidate pool, said the report, “A Guide to AI-Powered Recruiting.” Almost 75 percent of all job candidates, meanwhile, are passive. So, how do hiring managers and recruiters find these candidates? And then how do they best engage them?

A New Model

“Direct sourcing is more effective, efficient, and economically viable,” said the report. “A recent study by Lou Adler shows the number of applicants you need per hire based on the source channel. That is where the power of AI comes in.”

Historically speaking, voluntary turnover has been studied relative to job satisfaction and market conditions. But job satisfaction has been shown to be a low predictor – less than 15 percent – of voluntary turnover. “People will stay in a job for years even when they are unhappy,” said the report. “While labor market conditions do well at the aggregate level in predicting overall turnover rates, they don’t include enough information to identify turnover at the individual level.”

In the 1990s, a new model was developed that applied decision-making models and psychology to voluntary turnover. “Empirical research based on this new model found that two-thirds of the voluntary turnover they studied was initiated by some sort of shock or event that initiates the thought process that leads to voluntary turnover,” said the report. “For example, it could be that your company gets acquired or you get a new boss. In addition, we know that there are other key things that impact how susceptible someone is to a shock: for example, those that are newer in a job or already dissatisfied or have skills that are in higher demand.”

Leveraging Technology

This is the type of research that researchers have been testing and validating for the past two decades to continue to enhance the models and understand what impacts the decisions people make about leaving. “In addition, data scientists are able to leverage predictive algorithms and machine learning models that are continuously self-improving as more and more data is collected,” said the report.

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Recruiters and sourcers have always leveraged technology to help make their jobs easier and faster. And, of course, there is growing consensus in the market today on how HR can use artificial intelligence to find the right talent at the right time. “AI for recruiting is an emerging technology built specifically to reduce manual and time-consuming activities like candidate search, resume screening, and onboarding,” said the report. “Fifty-two percent of talent acquisition professionals say the hardest part of sourcing and recruitment is identifying the right candidates from a large applicant pool.”


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Simply put, AI is the simulation of human intelligence processes by computers or machines. These processes include learning from the vast amounts of collected data and using the applied rules to reach conclusions, and then self-correct. “In the area of human resources and talent acquisition, AI and machine learning are helping organizations drive value, gain prior unconceivable data-driven insights and pinpointing what matters across sourcing, hiring, managing, developing and retaining employees,” said the ENGAGE report.

Tough Questions

Businesses are facing disruption and transformation across technology, analytics, AI, automation, robotics and massive amounts of data. “As a result, the quality of their talent and the ability of these companies to extract the most out of their people is one of the most important levers at their fingertips,” said ENGAGE. “If you have the right type and amount of data on candidates, companies, markets, and industries and have the data science muscle, you can find relationships and correlations never seen before.”

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Among the questions that AI can help companies resolve include: When is the absolute right time to engage and target a candidate? What does one say to that candidate once you do engage? Is the candidate concerned about management issues at her current employer? Is the candidate working in a company with a rotten culture or poor work-life balance or her total compensation is below market?

Having access to data about candidates alone is not enough to find the necessary insights. ATS systems only go so far. “In order to get true insights to understand the entire job market landscape, you must look at data on everything that impacts that job candidate,” said ENGAGE. “That includes finding signals about the company they work for and the market that company is in and which industry the market belongs in.”

Data Journey

ENGAGE Talent dubs this the data journey. “Along the data journey there is so much data available that only AI and machine learning predictive insights can scale to the task of finding relationships and connections so you can get to the talent pool faster and more efficiently and with the right message and at the right time,” said the report.

Related: Five Ways HR Can Maximize Data and Analytics

Once a company identifies what is having the biggest impact on a given candidate, it can use that information to craft a message that will have the biggest impact on engagement of those candidates. “We are conditioned to delete all incoming messages because we are all inundated,” said the report. “The only time we would open messages in our inbox is if they are personalized and have some type of context related to us.”

If a potential candidate is going through major business shocks, he or she will be more likely to engage in a conversation and respond to an email that contains information about those shocks, such as leadership changes, litigation events or data breaches.

Validating Applicants

ENGAGE Talent, for its part, has developed tools that allow businesses to connect “the right candidate with the right opportunity at the right time with the right message.” Its proprietary scoring algorithms are able to identify the candidates that are twice as likely to respond to a recruiter as well as 63 percent more likely to change jobs within the next three months, said the company. These insights can provide a competitive advantage by allowing businesses to get to the talent faster and with the right message. ENGAGE describes itself as the world’s first AI-powered platform to combine talent mapping, competitive intelligence, passive candidate sourcing, and outbound recruiting in one candidate identification and engagement engine.

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“While businesses of all sizes have increasing amounts and diversity of data they can leverage to try to identify the best fit for each position, the recruiting process is still stuck in the past with inefficient processes and based on standardized resumes and biased interviewers’ opinions, and companies are suffering because of that,” said the report.


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AI-powered sourcing & recruiting seems to be able to help not only source but also validate applicants. “In fact, studies have shown that human recruiters along with predictive analytics and AI can outperform just manual recruiting processes alone,” said the report.

Data-Driven Insights

Artificial intelligence can help provide data-driven insights that humans cannot uncover by themselves. With AI, for example, companies can sift through thousands of resumes that would otherwise take hours. They can also screen job postings and descriptions for exclusionary or inappropriate language and help remove unconscious bias and inequality from the hiring process.

Related: Recruiters Face a Double Threat from Automation, But There’s Good News

Many businesses are using videos to assess candidates using AI, which is helping identify and quantify soft skills such as truthfulness and empathy. AI looks at word choice and inflections in a candidate’s voice to read between the lines, said ENGAGE. It can be also be used to source passive candidates and predict which of these candidates are the most likely to engage in an opportunity-change conversation.

Related: Hunt Scanlon’s Top 10 Artificial Intelligence Stories of 2017

Contributed by Scott A. Scanlon, Editor-in-Chief; Dale M. Zupsansky, Managing Editor; Stephen Sawicki, Managing Editor; and Will Schatz, Managing Editor – Hunt Scanlon Media

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