Talent acquisition, especially for those who interact directly with clients and candidates, requires strong interpersonal skills and the ability to put others at ease. However, even the best people skills won’t save you from the great number of time-consuming tasks involved in the hiring process. Given chores like sourcing and screening candidates, poring over resumes and coordinating interviews, time becomes a precious commodity for all talent acquisition professionals. And that’s where artificial intelligence (AI) technology comes in.
AI technology has been a game changer for talent acquisition. Thanks to a combination of AI capabilities such as machine learning, deep learning and natural language processing, talent acquisition pros no longer need to spend so much of their time on tedious tasks.
Instead, they can concentrate on who is the best fit for the role and organization, as well as any other hiring or headcount planning needs a client might have.
Improving Efficiency with Artificial Intelligence
Here’s how AI is beginning to streamline the talent acquisition process to save recruiters time and improve the experience for candidate and client alike:
Writing Job Descriptions
When ThinkWhy surveyed recruiters, 22% of them said they’d like to spend less time writing job descriptions. Much of what goes in a job description are the required qualifications. With so many similar roles with different job titles and skills that are likely to change, having job descriptions that incorporate reliable skills is a big time-saver.
Using a mix of machine learning and natural language processing, the salary answers feature of the software platform called LaborIQ® by ThinkWhy, for example, includes the required specific hard and soft skills that influence a job’s salary recommendations, and the forecast of how the salary will change over time. For instance, if a digital specialist is required to have skills in graphics or photo imaging software, the AI solutions would have identified this and placed into the hard skills category the need for knowing Adobe Photoshop, Adobe Illustrator or Sketch software applications.
In addition to skills, how potential applicants interpret the text of a job description is important. With so much attention now on attracting more diverse employees, more talent acquisition pros are using natural language processing software to write more inclusive job descriptions. By paying attention to word choice and candidates’ reactions to them, this software enables talent acquisition pros to create job descriptions that are more gender-neutral, and to avoid words that may bring up negative stereotypes.
When it comes to searching for viable candidates, AI has made the process easier. Modern platforms use AI technology to quickly sort potential candidates that meet your specific criteria, i.e. by keyword, location, job title, etc. So, whether you search multiple social media platforms or job boards for clients, AI sources a higher volume of candidates much faster than a person could on their own.
Screening Job Candidates
Another benefit is the ability to swiftly screen many candidates, rating them on how well they meet the qualifications based on their skills and experience. In addition, the most sophisticated software will mask any hints as to a candidate’s gender, race, class or other attributes that can lead to unconscious bias, which can lead to casting a wider – and more diverse – net for candidates.
Determining the Right Pay
Having accurate salary data can be your make-or-break moment when persuading an in-demand candidate to accept your salary offer instead of a competitor’s. Instead of relying on outdated information or being unsure of what constitutes market value in your city, solutions using machine learning and natural language processing, like LaborIQ, can now provide you with a salary range that considers location, skills, experience, industry and company size. Knowing the competitive salary range can prevent new hires from being poached by other companies and also give your talent acquisition team a realistic look of how much pay specific roles can garner, which in turn can help internal teams better budget for merit increases.
“The term AI has been overhyped, and many companies are touting it but not delivering,” says David Kramer, chief technology officer at ThinkWhy. “Modern TalentTech recruiting firms need to embrace solutions that are producing real results using these AI capabilities, or suffer delays in getting the right candidates to their clients as efficiently as possible.”
AI, it’s clear, will continue to enhance software solutions used for recruiting. The result will be an even more efficient talent acquisition process that saves many hours and multiple mistakes during the talent sourcing, screening and final selection process.
LaborIQ by ThinkWhy continuously monitors and forecasts labor data at all levels, measuring impact to cities, industries, occupations and business across the U.S.