Selected by Virtual Headhunters

Written by reputio | Published 2019/11/01
Tech Story Tags: artificial-intellingence | recruitment | headhunter-program | ai | good-company | latest-tech-stories | recruiting | headhunting

TLDR AI has become indispensable for great matches in recruiting for jobs. Every job that is advertised, attracts hundreds of resumes of hundreds of hopeful job applicants. For HR professionals, the most laborious part of the screening process is reviewing applications. Only 22% of those applicants succeed in winning an interview. The way people search for jobs is evolving too, in a world spiraling upwards to a tech high. Only 19% of job seekers currently use an app for their job search. The cost of recruiting, hiring and onboarding a new employee can be up to $240,000.via the TL;DR App

AI has become indispensable for great matches in recruiting for jobs
Every hiring manager dreams of bringing onboard the smartest of people. Former CEO of Apple computers, Steve Jobs, once said, “The secret of my success is that we have gone to exceptional lengths to hire the best people in the world.”
However, hiring the best people is the most difficult task imaginable. Every job that is advertised, attracts hundreds of resumes of hundreds of hopeful job applicants.  For HR professionals, the most laborious part of the screening process is reviewing applications.
According to recent studies, at least 118 job seekers on average, apply for any given job. Records also show that only 22% of those applicants succeed in winning an interview.
The way people search for jobs is evolving too, in a world spiraling upwards to a tech high. And while the job search is now at their fingertips, recent data from Monster found that only 19% of job seekers currently use an app for their job search.
Often jobseekers are frustrated by the amount of time they have to invest in applying for one job. Along with customizing the resume and cover letter, they have to fill out online, all the resume details again. Emailing the resume and cover letter alone has become a thing of the past. They little realize that Artificial Intelligence (AI) has changed the way recruitment takes place.
From another perspective, 52% of talent acquisition leaders say that the most difficult part of their job is screening the right candidates from a large pool of applicants. Hiring managers today, are aided to a large extent by hi tech involvement, eliminating the need for recruiters to go through thousands of resumes. They have the option of using tools such as an ATS or HR chatbot to screen candidates, and to match them with employer needs. In this task, skills matrices can help too.
In fact, many companies engage talent-management software to screen resumes, weeding out up to 50% of applications before a recruiter or hiring manager even looks at a resume or cover letter.
Not only that. Bots are faster and more efficient at scanning resumes. Studies show that human beings spend an average of six seconds looking at a resume before making a decision. The bots examine resumes more carefully, and also seek out candidates' social media profiles and compare them to the needs of the job applied for.
As it happens, employers cannot be too careful in the initial screening process through AI, because human error can be very expensive. Jörgen Sundberg, CEO of Link Humans, an employer branding agency in London, said,
“The  cost of recruiting, hiring and onboarding a new employee can be as much as $240,000.”  
Arte Nathan, founder of The Arte of Motivation, a human resources advisory service based in Las Vegas, said,
The cost of a bad hire is always extensive. Most companies don't know the full cost of the turnover, so they don't apply the resources upfront to avoid it. If you make a bad hire, there is a ripple effect among all who work for you, your product and your product quality."
Brandon Hall Group, a human capital research and analyst firm based in Delray Beach, Fla., identifies several other costs of a bad hire, such as, recruitment advertising fees and staff time, relocation and training fees for replacement hires, negative impact on team performance, disruption to incomplete projects, lost customers, and  weakened employer brand.
The hiring process is generally up to six weeks and costs over $4,000.  Therefore, enhanced accuracy in matching skills offered and skills needed, can clearly reduce wasted time and resources, and positively impact a business’s bottom line.
To address this need, the recruiting platform, Woo, has spent two years and $7 million, creating a scalable virtual robot called Helena, to help companies make the perfect hire. When Helena is given the opportunity to single-handedly do the matchmaking, it has been found that the end result yields more powerful matches than if both parties (employers and candidates) try to find a good fit.
Helena had been built by a team of brilliant data scientists and highly skilled recruiters. The taught the robot headhunter how recruiters thinks and make decisions.  They also created a framework to model the intricate and interconnected technologies.
Tracking performance of selections, providing consistent feedback and ensuring machine-learning, appear to have made Helena a smarter virtual headhunter, with results vouching for the headhunter’s capabilities. 52% of candidates Helena chose, got interviews – which was three times more than recruiting agencies, who only got interviews for 20% of candidates. Helena is also 20 times better than online job boards.
Despite, this undeniable success of AI, the globally-reputed audit firm  KPMG, states, in The Future of HR 2019, that only 14% of companies invested in AI for HR over the past two years. 50% of companies surveyed, admitted they were “not at all prepared” to respond to such a situation.
Geoff Livingston, dubbed by the Washington Post as a local blogging guru, says,
“I see the movement towards AI and robotics as evolutionary, in large part because it is such a sociological leap. The technology may be ready, but we are not – at least not yet.”

Written by reputio | Covering disruptive stories
Published by HackerNoon on 2019/11/01