How artificial intelligence can handle the mundane and free up recruiters to act more strategically.
By Ian Cluroe
The great promise of artificial intelligence (AI) taking over many day-to-day tasks is finally a possibility for the majority of organizations. Take a look at the impact AI has in the healthcare industry. Based in Pittsburgh, Aetheon manufactures TUG robots, which transport medications, meals, linens, and other supplies to 140 hospitals in the United States. That’s 50,000 trips each week that would have otherwise been performed manually. Aetheon estimates that the automated delivery and tracking of these items by TUG robots can lower the cost of delivery between 50 and 80 percent while enabling clinical and service staff to focus on what matters most: patient care.
On the other hand, AI is a concern for many—workers worry that robots will eventually make their labor-intensive, task-oriented jobs redundant, leaving them in the unemployment line. Earlier this year, the World Economic Forum reported that a net five million jobs would be lost as a result of technological change—primarily robotics and AI—in 15 major developed and emerging economies by 2020.
This translates to many industries. Recruiting, for example, has a fair share of manual work that is a prime opportunity for automation. But it’s also a knowledge-based business, where success is based largely upon cultivating trusted, personal relationships. So where can AI step in?
First, the low-hanging fruit: efficiency. There’s no question that AI can dramatically reduce, if not eliminate completely, most of the administrative tasks that eat up a lot of time and productivity in a recruiter’s typical day:
• Stacks of applications and resumes can be sifted and qualified more quickly and accurately using algorithms that parse based on criteria like key words and phrases, location, availability, employment status, and salary history.
• Candidate data can be audited and cleansed more quickly and accurately.
• HR departments can provide executive management with more accurate and timely reporting on their recruitment performance.
• Intelligent systems can help schedule, reschedule, and track interviews and appointments.
• Candidates can be kept up to date about the progress of their applications.
The payoff? Dramatically reducing the delays and human error that hinder productivity and can sometimes give recruiting a bad name. Better accuracy and less wasted time means that recruiters can focus on building better relationships with their two most important constituents: hiring managers and candidates.
Uncovering Hidden Gems
Traditional job sites are replete with inactive or incomplete profiles that present a poor picture of job seekers’ true skills and experience. That’s a pain for recruiters who scour these resources in an effort to find and connect with quality candidates. And it’s a lost opportunity for candidates whose true value is underrepresented by inflexible platforms.
But companies like Connectifier—launched by former Google engineers and acquired earlier this year by LinkedIn—are using AI and smart search algorithms to search across a myriad of public sources to build more complete profiles of hundreds of millions of candidates.
Finding people based upon what finite sets of skills they’ve checked—or haven’t—on a list is no longer status quo. Recruiters can now look at their social media feeds, what blogs they’ve written, what conferences they’ve spoken at, and what user groups or message boards they participate in.
In doing so, organizations can build a better picture of each candidate, including how best to reach them—which is no small task in itself! What’s more, because these profiles are built in real-time, AI can identify candidates who are most qualified and may not be actively searching.
So far, AI has been used primarily in the pre-interview stages of the recruitment process, focused mainly on data optimization and process efficiency. But that’s starting to change.
One of the most valuable skills of an effective recruiter is an ability to read someone, based not just on their words but also on the nuances in their speech, their expressions, and their body language. In most situations, recruiters can make an accurate judgment about a candidate’s potential to succeed in a role based on how they present themselves during an interview.
Now we’re seeing this same ‘intuition’ in the guise of AI. Video interviewing technology from companies like HireVue, for instance, can assess a candidate based not just on the words they use, but also their facial expressions, the tone of their voice, changes in their facial temperature, even pupil dilation. AI can incorporate literally tens of thousands of data points to draw correlations between the way a candidate communicates and their potential for success in a given position, based on empirical evidence. What’s more, the use of AI can dramatically reduce the potential for human bias to creep into the decision-making process.
Ripe Passive Candidates
Timing can be everything in talent acquisition. Knowing precisely when a candidate is ready to pull the trigger on a move can be the difference between a filled requisition and one that lingers too long or is filled by a less-than-perfect hire. But knowing when to engage with highly qualified passive candidates is a tough challenge for any recruiter.
Joberate is working to make that judgment call easier. Its platform takes public data available through social media and combines it with machine learning and data analytics to create a simple score that illustrates an individual’s job-seeking behavior. This can be aggregated to the corporate level and shows how likely employees are to leave.
This has at least three potential applications for today’s forward-thinking HR department: First, it makes it possible to predict how warm a passive candidate might be to an approach from a recruiter. Second, it helps organizations pinpoint potential areas of vulnerability in retaining its own employees. Third, it can identify competitors whose employees are high-potential targets for an approach.
Job ads are ripe for AI disruption. It’s been proven over and over again—at great expense—that an ad could reach a million people, but if candidates immediately tune it out, it’s basically throwing money into the trash.
Why do candidates ignore ads for perfectly good jobs? It can be boiled down to a few reasons: they’re dull, full of corporate jargon, uninspiring, and the job description might even be intimidating. Seattle-based Textio is one company that is tackling this challenge. Its AI works like a supercharged spell checker, looking for patterns that will make a job ad resonate with readers and can even show if it turns them off. It assesses variables like text, fonts, image placement, and active versus passive language. Based on outcomes, data from tens of thousands of previous job ads, and a back end that combines machine learning, natural language processing, and statistics, it predicts how well an ad will perform and suggests ways it can be improved, all in real-time.
When all is said and done, the degree to which any technology is adopted is driven by one of two things: how it can help organizations save money or make more of it.
In the talent acquisition profession, there are a lot of administrative-heavy tasks. When talking to hiring managers and recruiters alike, few would argue that those tasks make people more effective, but they still have to get done.
Implementing technology that frees up recruiters to do things that add more value to the talent acquisition process is always worthy of consideration. They can spend more time with hiring managers to understand their business, their talent needs, and how to ‘sell’ a role to candidates. And they can spend more time nurturing candidates and closing those deals.
It’s all about growing relationships and helping recruiters move away from managing ‘the machine’—because it can now manage itself.
Ian Cluroe is head of global marketing for Alexander Mann Solutions.