Artificial intelligence (AI) has become a core selling point in applications which serve nearly every industry. Over the last few years, it’s become more widely adopted by the human resources and recruiting communities as a powerful tool in the hiring process. From a more engaging initial job listing to a more streamlined interview process, AI is helping recruiters drive their hiring strategy into the future.
Posting a job
Hiring has become more social in the digital age. Platforms like LinkedIn in particular, have seen an influx in activity from both sides of the recruiting process. Recruiters and job seekers alike, flock to the platform due in no small part to the AI tools powering its growing network and job boards.
When it comes to posting a job ad with the most impact, how a recruiter describes the role and necessary qualifications directly correlates to the level of talent that who will apply to the position. Software that leverages AI to create compelling listings has become increasingly popular. By analysing the content of successful job postings, these solutions enable recruiters to emulate the terminology and structure being used to fill highly competitive roles.
Sourcing and screening job seekers
With more than 12 million open job seekers on LinkedIn at any given time, initial pre-screening would be an arduous, if not an impossible task for a recruiting team, if done manually. Luckily, one core functionality of many AI-powered recruiting solutions is targeted job seeker identification, through a variety of predetermined characteristics; such as education, prior experience, location, and other qualifiers.
Once job seekers are selected from a total pool of applicants, their resumes must be sorted. Software solutions that automate the resume screening process have become more popular recently and have led to greater understanding by job seekers, line managers and recruiters alike, about the types of core competencies, experiences, and role specific keywords that make up a strong job seeker profile.
The interview process
Once a recruiter or a line manager has a list of interviewees, they can commence their interviews. Job seekers can get frustrated when the process is perceived as being too slow. Hiring managers and recruiters don’t want to be overwhelmed. Using AI-driven software to help schedule optimal interview times helps move the process more efficiently and can reduce time-to-hire timeframes. Interviewees can select from a list of times, choosing what works best for them and the AI tool will automatically populate a calendar invitation for the recruiter or hiring manager with all the necessary information. This can be especially useful if a job seeker has to reschedule, or if one interviewer takes the place of another.
What if recruiters could collect hiring data which would inform the recruiting strategy in the future? Machine learning (ML), an offshoot of AI, promises to do exactly that. ML algorithms use historical data to build regression and classification models, determining the correlation between a set of variables or classifying factors to hiring outcomes.
For example, a recruiter or hiring manager could use predictive hiring software to more accurately identify qualities of ideal job seekers, when implemented into the recruiting process, reduce the time-to-hire and voluntary turnover, saving time and money per future employee. On the HR side, predictive analytics can also be used to isolate behavioural triggers that may indicate when an employee is dissatisfied and may seek to leave, leading to more proactive retention and conflict resolution strategies.
AI solutions are intended to augment the existing skill set of recruiters and hiring managers. This evolving technology will hopefully free up recruiters to focus on higher level strategic tasks, by decreasing the time to hire and ultimately reducing costly missteps in the hiring process.