Now Revealing Three Areas of Recruiting Proven To Be Improved By AI

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Savvy business owners are evaluating which areas of their company to implement AI. Are you? Many companies have had success using  artificial intelligence, (AI) to reduce operating costs and increase sales. One area quickly gaining momentum in AI is HR.

Imagine how much more focus your HR team could dedicate to your strategic priorities if they were able to conduct interviews without doing the mundane tasks of emailing and confirming dates with candidates. According to a SHRM report, the average time to fill a position is 36 days, and the average cost per hire is $4,425. Implementing AI could reduce those numbers, in fact, some businesses who’ve implemented AI in their hiring process reduced their cost per screening by 75 percent. 

Whether hiring for a large organization or a start-up, using old methods of finding the right candidate can be an arduous process. Based on our research, not actual use, we’ve selected a few companies offering AI integrated software being used in recruiting. If you want to improve your hiring ROI, read below to learn how your company can use AI to source, schedule, and interview more efficiently.

1. Sourcing

Is your HR team only posting job descriptions on job boards and relying on candidates to find your open requisition? Are you missing out on optimal hires because the number of resumes received far outweigh your manpower or technology’s capabilities?

AI software aggregates and stores data containing the skill sets and characteristics of successful employees of a company. From this data, AI platforms use algorithms to create a model from which it compares all candidates, then the system searches the internet and matches the best candidates.

Has your HR professional’s search ever returned what appeared to be a great match, only to find out that the person is happily married to their job and not interested in your position? The solution is to use AI systems that provide predictions about who would be more likely to leave their current role and which candidates to contact first.

Some platforms offer databases containing millions of candidates, with the option to use your own applicant tracking system (APT). The larger and cleaner the data set (candidate pool, characteristics of successful current employees, Etc.), the higher the probability of a successful hire.

Other software allows your team to provide feedback on how closely the algorithm’s selection matches the recruiter’s desired candidate. There’s also software, like Allyo, that captures post-hire feedback. The machine then learns from the feedback, increasing the tool’s ability to provide better recommendations over time. In addition, AI can recommend applicants for other open positions for which they are better suited.

You must also consider the ability to obtain a diverse candidate pool when evaluating AI-based recruiting software. Ask the vendor what process they use to source diverse candidates. Some systems analyze data points within an applicant’s profile, such as schools, and memberships within diverse organizations. Other systems, such as  Textio, analyze job descriptions to choose words that attract diverse candidates.

One benefit of using AI technology is that more applicants at the top of the funnel make it through to the interview, which could result in a more diverse candidate pool, although this process still may not be as effective in generating diversity. The data scientist must design the algorithm to look for characteristics that represent more than the typical profile of the existing successful employees in the company, especially if the majority of the employees are Caucasian men.

2. Scheduling

“I sent a message to the candidate.” Does that sound familiar? Has your company been using the same methods to schedule interviews for the past 20 years? Newer AI-infused technology, i.e,, (not to be confused with the ever-popular, enables your HR professionals to use a meeting assistant to schedule interviews very much the same way they would with a human; think Siri or Google. It uses natural language processing to schedule meetings with applicants on a variety of chat platforms, such as SMS, Messenger, and email. It uses an intelligent algorithm that automatically finds the best time to meet (based on the requirements you set).


Once the interview is scheduled, the exclusive People Insights feature of helps your HR team prepare for the interview by providing them with 2-3 pages of relevant information on your candidate’s interests and personality. It obtains this information by analyzing public data on their social media accounts.


Automating all of these tasks speeds up the hiring process, creates a better candidate experience, and gives more time back to hiring managers and recruiters to do non-routine work that involves more soft skills.

3. Interviewing

As a tool to conduct interviews, much like described above, facial recognition technology uses algorithms to find candidates whose profile most closely align with those that are currently in the role, or those who’ve had success in the role.

The technology records the interviews. It analyzes responses and uses an algorithm to assess facial expressions; for example, how wide the candidate’s eyes open, lips tighten, or eyebrows rise, which might indicate their level of sincerity. The voice recognition software evaluates the person’s words, such as the use of passive vs. active words; and speech patterns, such as speed and tone, to determine if the person fits with the company’s culture.

Although this technology has proven to be a great asset, facial recognition software has faced criticism due to the biased results it has rendered, especially in people of color. When used to determine the right fit for hire, it could limit the success rate for people of color. Just like discussed above for sourcing, if the training data , (in this case, the company’s current employees) used to create the algorithm lacks the diversity needed to yield a good match, it will reject people of color. Hiring managers must use careful judgment when using facial recognition as its sole method of ruling out a candidate.

In general, AI intends to reduce other biases that could result from the manger’s preferences. Qualified candidates that might not have gotten a seat at the table may now have a chance. Now the manager’s only challenge is meeting with the individuals and choosing between multiple qualified candidates, all of whom would be great in the role.

When you’re ready to gain access to a broader range of suitable candidates in a more time and cost-efficient manner, incorporate AI into your recruiting efforts. If you need help evaluating its benefits or are unsure of what to look for in a vendor, contact AI Business Partners. We’re here to help.

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