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How AI makes hiring more accurate and personal

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AI is projected to catapult from a $643.7 million market today to $36.8 billion by 2025. Bersin by Deloitte calls it one of the ten major trends changing everything about how we build and manage the world of work. It’s becoming an incredibly powerful tool for recruiting, though not always understood. There are two questions I often hear:

  • How can we use AI to better match skills to openings?
  • How can we use AI to make the entire recruiting and hiring journey better, and improve candidate experience?

Before delving into specifics, consider this: Essentially, if A, then B. Just as AI is changing the game, we have to change how we see it: it’s a tool with multiple benefits at once. In other words: if we are better at sourcing the talent to find those with the right skills to match the right job opening, then the candidate experience will be better.

In this regard, AI is a positive disruption that not only improves how we find candidates, but how they experience the process of being found. All along the recruiting journey it works faster and more efficiently by profound degrees. And at the same time it has a tremendous impact on candidate experience. Let’s look at common pain points to recruiters and candidates and see how AI improves the outcome:

Recruiter Pain Point: Too Many Applications

A common pain point among recruiters is the sheer onslaught of digital applications — whether or not an applicant is actually qualified, with the required skills. We can’t put too fine a point on this: Job seekers spend an average of 49.7 seconds reading a job description, and 14.6 seconds of that is spent on the actual requirements of the job. Then, many just hit send. According to Glassdoor, each corporate job offer attracts 250 resumes on average. Of those, four to six are called for an interview — and one gets the job. Getting from 250 resumes and 4 to 6 callbacks per job is a whole lot of sorting.

AI Solution: Finding Soft Skills

AI can use pattern matching to connect the dots between job requirements and the skills and training listed on a resume. Machine learning means that AI can also get better at this the more it works, from building a bank of alternate phrases and variations it recognizes to tailoring its rankings to factor in other criteria. And AI can find soft skills just as quickly as hard skills. For instance, consider Arya: this new AI recruiting platform learns who the ideal candidate is through a combination of machine learning, big data and behavioral pattern recognition.

AI Solution: Assessing Fit

AI can also take an extremely educated and predictive guess about how a candidate may do in the long term, addressing concerns about ROI without bias. AI can use past hiring and employee records and patterns to get a clearer picture of the relative success and fit of a hire — and can identify potential blind spots of training gaps, enabling companies to put the services in place that support a better outcome.

Candidate Pain Point: an Overlong Application Process

Let’s face it: the digital environment has changed many job applicants’ perception of time. To a candidate in this digital environment, hours feel like days and days like weeks. Time, particularly for digital native generations, has shrunk — and the etiquette of responding to a message has radically changed. This is just one point of friction out of many in terms of how a candidate experiences the application process today. A delay in getting notified can feel like a rejection even if it’s not.

But while recruiters famously spend an average of 6 seconds reading a resume, finding the right hire for one job may take more than 20 hours. (And rare indeed is the recruiter tasked with filling one job at a time.) The wait — particularly if a candidate has been contacted by an organization’s hiring team — can feel like a hurry up and wait hustle, and may sour a candidate experience. Whether the result is a turn towards a different employer, or simply an element of disengagement in the process, it can stop a recruiter-candidate relationship before it starts. But recruiters simply don’t have the time or, most often, the person power to contact every applicant every step of the way.

AI Solution: Recruiters Don’t Do the Heavy Lifting

Allocating the heavy data sorting to AI frees more time for reading the resumes that actually matter. It means that unqualified candidates can be notified faster, and qualified candidates are really qualified — and the recruiter has had more time to spend getting to know them on paper before an interview. But additionally, AI can work as the messenger. For example, when a promising candidate is found with the qualifications and skills that match, Arya can reach out with a personalized message. If a candidate is interested, the connection has already been made — and a recruiter can take it from there. Instead of radio silence, there’s AI at work for you.

The myth that AI-powered recruiting is impersonal and inaccurate is just that: a misassumption about the power of AI. With the ability to greatly increase searches to radically cut down on searching time, as well as a way to reach out and develop a talent pipeline, AI enables recruiters to get back to what they know how to do best: spend time getting to know promising candidates, and find the best fit for each job. And for candidates, AI enables frequent contact and a faster process that improves their experience — and may just affect their decision to join your organization.

This post was published first on TalentCulture.

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