Through processes like automated candidate sourcing and candidate rediscovery, AI sifts through many resumes to find those most suited to a position.
The use of machine learning and AI in hiring remains limited despite great potential. Companies have been hesitant to embrace the technology but are increasingly seeking ways in which AI can improve their recruitment and retention in a competitive job market.
A recent HR.com survey identified locating, acquiring and keeping candidates as major challenges in the hiring and retention process. On average, companies would not rehire 31% of their recent hires if given the chance to do it again.
Only about one quarter of the surveyed companies report that their recruitment technologies met their current hiring needs to a high or very high extent. Companies also expressed their desire to minimize time spent sorting through resumes and finding a proper list of candidates. Both issues can be addressed through the utilizing AI in hiring procedures.
Bring the right candidates in
Through processes like automated recruiting the field can be whittled down to a more manageable number of candidates. Companies can couple this with a process known as candidate rediscovery in which an algorithm can sort through people who have shown interest in similar positions before and select those who are a viable option for the new role.
Typically, the process of locating and narrowing down a field of candidates is the most arduous of the entire process. This is where AI can and should be implemented, but with at least some human involvement.
“Machines can quickly narrow a wide array of outcomes and data down to a handful of choices,” Will Hayes, CEO of Lucidworks, an enterprise search technology company based in California, said.
Allowing the more tedious tasks to be handled by AI in hiring not only permits employees to focus on other tasks but these algorithms and chatbots can handle larger candidate fields in less time, an advantage in a competitive market.
Rainerio Borja, President of Alorica Asia Pacific, has seen the introduction of AI in his company and its usage in recruitment. For Alorica, the usage of AI works to supplement their recruiting process and ease the burden on employees.
“We implement technology to free up our employees to focus on more complex and customized tasks, while AI handles the simple, repetitive ones,” Borja said.
Get to them faster
The job market is flying — there are often more positions than there are job candidates. Companies seeking employees must quickly provide a worthy offer, or they risk losing out.
“Speed is critical. One of the things that machine learning can do is get you to hire faster,” Dr. John Sullivan, HR thought leader and author, said. “The top people are going to be gone in 10 days.”
One solution to this increased need for rapid acquisition are chatbots. These can locate potential job candidates for open positions in much less time than a human alternative. Turning to chatbots to help locate interested and proper candidates leads to better options when it comes to filling open positions.
“By utilizing chatbots to initially screen candidates, it has allowed us to cut down on the time that it takes to determine if an applicant qualifies for the next round of interviews,” Borja said.
The traditionally lengthy process can therefore be cut down with AI and potentially provide more suitable candidates.
Finding the needle
The usage of chatbots and machine learning can find jobseekers who may have been passed up by previous methods. In new companies or those with shifting priorities, the traditional ideas of seeking the candidate with the most education or experience has changed. As Sullivan sees it, those individuals who don’t have a degree but who have a body of work within a certain field may have been passed by when using traditional methods. AI can be tuned to count candidate’s abilities rather than formal education.
The technology is only as capable as the data and parameters it is given. Traditional markers of success and capability may not be as representative as once thought — now, higher intelligence and general cognitive ability are the best determinants of job performance, rather than education specifics. It would therefore be necessary for companies to tweak their AI to look for these when it hunts for candidates and that these companies track the details behind successful hires and unsuccessful ones.
Despite the advances in technology, only a small percentage of companies utilize performance data when it comes to their hiring process according to Sullivan. If you don’t track what made candidates succeed and what did not and then inform your machine learning algorithm to look for the successful qualities, then it will just repeat mistakes.
What the future of hiring and HR looks like
The adoption of change and embracing of AI in hiring has been slow to this point, but the potential benefits are still there. The process requires the data and companies must track the performance of hires (retention, effectiveness, cultural fit) and compare where these optimal performers came from. They must be able to understand what makes a good candidate when it comes to the company they run. Who has succeeded, who has struggled and what do the positive candidates have in common?
AI, machine learning and numerous other technologies can help with that, as well as improve the speed of hiring and ease the burden on their current employees.
“Deploy AI projects iteratively, where you can take bite-sized chunks with measurable outcomes to ensure you don’t over-promise and under-deliver,” Hayes said. “Focus on the small victories and they’ll inevitably lead to a major positive impact.”
Written by Joseph M. Carew, this article originally appeared in SearchEnterpriseAI: http://bit.ly/3aRbeR2.