The primary component of George Jetson’s job was to sit in front of a giant…
As AI recruiting continues to establish itself as a trajectory-changing force in the world of HR, the time has come for us to empower ourselves with knowledge. Between thought leaders, business practitioners, HR and hiring decision-makers, there is much to learn from the experience and the results from others, as they embrace automation and align their workflows with the bottom line business mission.
One of the meaningful differentiators between an excellent hiring experience and a mediocre one is having a reasonably short time-to-hire between the first interview and an offer being extended with a firm start date. For organizations concerned about their recruiting metrics, unfilled jobs are a severe drain on productivity and reflect poorly even on their best-intended efforts. This is an area in which recruiters are wise to draw inspiration from other functions and industries to reduce hiring times, improve their candidate experience, and maximize their KPIs across the board.
For example, in healthcare, something called a survival analysis machine is utilized to analyze the time to an event, such as the time it is expected for a patient's disease to relapse, or they are likely to die. The analogy to recruiting is that similar analytics can be used to predict how long a job will take to fill, the overall performance of the job market, and how long a job is likely to remain full or eventually turn over. Processes like this allow recruiters and HR leaders to manage the expectations of a client, a candidate, or the c-suite by offering calculated measures of when they can expect a position to be filled with a qualified applicant.
Finding the Ideal Candidate (For Real)
For some progressive recruiters, AI, automation, and machine-learning are well-matched partners in the search for a perfectly qualified and thoroughly vetted hire. This goes beyond the standard reference and background check. Thanks to programmatic recruitment solutions, hiring organizations can reverse engineer a candidate's fit in their corporate structure and even predict their potential performance.
Ideally, these automated processes start with the gathering of resumes on a dedicated virtual system, work samples, recommendations, and other relevant documents from candidates. An organization can then either work with outside vendors or internal experts to create a unique algorithm to match prospects with the specific needs of their companies. Alongside traditional reviewing and job advertising strategies, this can help give a well-rounded perspective on an individual's suitability for a role.
Interviewing with Ease
For a long time, interviewing has been one of the costliest and time-consuming aspects of talent sourcing -- both from a labor and overtime perspective and from an overall budgetary one, accounting for travel and lodging. Now, there's no need for candidates to board flights or shack up in a hotel during the preliminary evaluation stages for a potential job. Instead, AI and automation have made possible for recruiters to interview candidates on their own time, record these interactions for later analysis, and even superimpose more robust technologies, such as facial recognition to gain more profound insights into the suitability of a potential employee. While still in its early days of use, AI-powered facial mapping technology to interpret employee feelings and disposition is increasingly being used by more recruiters to find ideal skills and personality matches for specific roles.
Tracking Down Passive Candidates
According to data from LinkedIn Talent Trends, about 15% of currently employed individuals are toeing the waters of a new opportunity at any given time -- exploring their networks and keeping their ear on the ground for open roles. Even more surprising; an estimated 80% of employed professionals are at least open to discussing other potential opportunities. Recently, recruiter tools have been released that offer hiring organizations valuable insights into how likely a passive candidate will be to entertain a discussion about a potential career change. Specific "predictability signals" can let hiring organizations gain insights into whether those coveted already-taken professionals are discreetly on the new job hunt and may jump ship for a better offer. These tools use natural language features to gauge interactions between recruiters and candidates.
Not Replacing Jobs, But Optimizing Them
While many fear that AI recruiting and automation will soon replace HR jobs, the fact is that these new technologies are helping us to be better at our jobs, and eventually, perhaps even creating new ones. Instead of fearing AI, start seeing it as a job-transformer and your strongest ally in the war for talent. Most importantly, AI reduces the workload of tedious, repetitive tasks that people tend to be bad at or have a high margin for error, such as reviewing resumes and crunching massive swaths of data.
For time-crunched HR leaders, the next natural task to partially outsource to a robot will likely be job board. AI is rapidly changing candidate sourcing by managing job board content distribution, advertising spends, monitoring performance, and KPIs all from one platform.
With today's competitive hiring landscape, it's only natural that a recruitment professional would hope to connect with hundreds of thousands of potential applicants while maintaining the ability to pare these selections down to only the most qualified individuals. With programmatic job board advertising, this is all possible and so much more. Create white label job sites to improve the candidate experience. Connect prospects with employers efficiently with real-time job matching. And see how data-driven algorithms can help you target the right job seekers at the right time.