You are currently viewing Human Capital Management: AI Can’t Replace the Human Side of Recruiting

Human Capital Management: AI Can’t Replace the Human Side of Recruiting

What happened to coal miners is not going to happen to recruiters.
Automated and autonomous technologies have forever changed mining globally, and no amount of tariffs or corporate handouts will alter the reality that coal extraction requires fewer and fewer people. Donald Trump’s 2016 campaign blamed the sharp decline in coal mining jobs on Democrats and coastal liberals, yet overlooked technology’s role in eliminating them for good.
Recruiting is another industry in which the introduction and adoption of new technologies has become commonplace. An important difference is that recruiters are not—despite working in an industry hungry for efficiency gains—facing the same fate as miners or those who used in work in offices such as bookkeepers, accountants, secretaries and admin staff. The demise of those positions was due to software and hardware innovation; QuickBooks eliminated hundreds of thousands of bookkeeping jobs, while word processing and other desktop software apps made secretaries almost extinct.
Recruiting is Different
The principal reason why recruiting will avoid the same fate as the West Virginia coal miner or Southern California bookkeeper is because it’s fundamentally different. Recruiting isn’t just a sequence of tasks; it’s a sequence of tasks with a necessarily heavy human component. Recruiting comprises engagement and communication with other HR team members, hiring managers, executives, other employees on hiring teams, along with external contacts such as job sources and agencies. To that list we can also add the most important cohorts, prospective employees, applicants and candidates.
The Rise of the Machines that Learn
In referring to technology, I’m not referring to software programs like Applicant Tracking Systems that have existed for over 20 years. I’m referring instead to advances in Artificial intelligence (AI) and Machine Learning algorithms that are both promising to some and frightening to others. For reference, Machine Learning is the idea that we can feed large amounts of data into a computer that will identify patterns and uristics almost by itself. Once identified, it will apply the “conclusions” to new sets of data. AI is the broader concept of machines being able to carry out tasks in a manner that we consider to be “smart.”
Much of the promise of AI/Machine Learning lies with introducing more objectivity into recruiting, handling more data and automating as many processes as possible. AI and Machine Learning are great for all of those. What they’re not great at, and will not become so in the foreseeable future, is replacing face-to-face human interaction.
Let’s face it, most candidates want personal interaction when seeking a new opportunity. New employees are not just filling an anonymous opening on an org chart; they’re seeking opportunity, challenge and a work environment where it’s not all about work. There’s a selection process on both sides before it leads to buy-in, and there’s only so much application of technology you can make when candidate courting becomes conversations across tables in boardrooms and restaurants.
Improving a Recruiter’s Favorite Metric – Time-to- Hire 
I think it’s important to understand that adoption of AI in recruiting is not an either/or reality; It’s still early days but recruiters are already benefiting. By observing how managers and recruiters make screening decisions, AIbased systems can predict the match between a job, a candidate, and a team:

  • Submitting an application will become much easier for candidates.
  • Recruiters can evaluate resumes and candidates faster.
  • Ensuring position fit is more precise.
  • Identifying the best candidates in a candidate pool takes less time.

The cumulative effect of AI in these areas is that time-to-hire is significantly reduced. Recruiting teams can make internal decisions, close job requisitions faster and reduce the potentiality of poor hiring decisions, all of which happens in a manner that fully respects candidates.
Enhancing the Candidate Experience
The other side of AI-enabled recruiting is the candidate experience. From seeing what our customers are doing, we know that a great candidate experience equals an 80% greater chance that the candidate will accept an offer. What’s the secret of delivering this kind of experience? Respect the candidate, be transparent and don’t keep them in the dark. For example, don’t ask candidates the same questions multiple times in interviews. Keep recruiting stages short, precise and respectful. Our customer data show that these characteristics increase job acceptance.
Driving Improvement Using AI and Machine Learning
Whether you have a lot of AI and Machine Learning experience or your education is starting with this article, here are a few specific source-to-hire applications where smart systems deliver empirical value:

  • Helping you optimize your marketing budget and how you allocate the money and collect resumes. Analyzing your and other companies’ data will allow smart systems to understand where and when the budget should be invested, significantly reducing the cost-per-hire and increasing candidate quality in your pipeline.
  • Ensuring that candidates who are not a fit are treated respectfully and receive professional and courteous notifications about their candidate status.
  • Matching an application to a job description, a candidate to the company culture, or a hiring manager preference to an existing profile in your candidate database can deliver huge value.
  • Making these promising matches, pushing the right candidate to the top of the list, and automatically handling interview scheduling deliver important topof- funnel returns.
  • Enabling interviewers to become more professional by surfacing the right type of questions according to the position and job. Process-driven interviewing like this will enable companies to avoid expensive hiring mistakes.
  • Following the process and suggesting follow-up actions to the hiring team.

These applications and others will make AI tremendously useful to recruiters in the next several years. From collecting applications, evaluating resumes and making decisions, its impact will be massive. By applying automation and semi-automation to so many different recruiting tasks, recruiters will gain many more hours for the kind of human-to-human interaction that reveals the type of information and learnings that software and data can’t discover. And, depending on the region where they’re working, recruiters may be able to help ex-coal miners find new career paths with more long-term upside.
About the Author 
Omer Tadjer is the CEO and Co-founder of Comeet. He has been involved in high-tech companies for more than 15 years, a decade of which was devoted to software development and managing development teams. A technologist and philosopher by training, he is a business entrepreneur at heart. He is passionate about applying his practical IT and management experience to creating valuable products and transforming the way the HR industry operates.