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Five Use Cases of Artificial Intelligence in Talent Recruitment

One of the biggest challenges facing enterprises today is in finding the right talent and making the right hire. Imagine the huge, and significant costs arising from hiring a wrong person. Given the large volume of data available about potential prospects as well as in-house talent, Artificial Intelligence can be used to improve efficiency and efficacy of new talent recruitment.


When it comes to talent recruitment, the lifecycle remains pretty consistent. With each new recruitment cycle, large amount of datasets get created, but not captured for future reference. Every single time, enterprises look for new talent, they repeat the entire lifecycle of talent recruitment, beginning with posting a job, to sourcing, screening and appointing one of them.

Enterprises end-up losing time and talent, everytime they seek to find fresh talent or replace existing employees.

Some of the key challenges arising from talent recruitment include the sheer volume of digital applications that enterprises receive, with a significant amount of noise, meaning, no clarity on whether candidate has the right skill-sets or qualifications for the job. On the other hand, the candidate’s awareness and perception of time has also changed. For today’s digital natives, the lack of acknowledgment or progress update on a job application, could be translated as a rejection. This, in itself, could lead to friction between candidates and potential employers.

Two key questions arises, and this article tries to answer them:

  • What role can Artificial Intelligence play in ensuring a better match between available skill-sets and job openings?

  • How can Artificial Intelligence be leveraged to make the recruitment process easier for enterprises, while enhancing the candidate experience and delight?

As per recent KornFerry survey insights from APAC, the use of Artificial Intelligence as a sourcing tool has been cited by around 70% of the talent acquisition professionals. In addition, 64% of the respondents in APAC confirmed that AI has significantly changed the nature of talent recruitment in their firm.

Here are five different use cases of Artificial Intelligence, as demonstrated by AI startups from across the world.

Robot Vera

St.Petersburg-based startup, Robot Vera, created an artificial intelligence software designed for recruiting. Vera fastens the vetting process of high-turnover and blue-collar job positions, significantly cutting down on the time and cost of recruitment. Vera can interview hundreds of applicants simultaneously via video or voice calls, narrowing the field to the most suitable talent pool, of around 10%.


Toronto-based ClearFit enables recruiters to save sourcing time by automatically finding and ranking candidates with its patented job-fit technology that instantly identifies which applicants match the employer's needs.


San Francisco-based company Mya, a conversational AI-recruiter, aims to address inefficiencies in recruitment processes, while improving the delight for both candidates and recruiters alike. Mya operates by learning to interact and communicate with a candidate, as well as, integrating with the current applicant tracking system (ATS) of the enterprise. Mya periodically updates the candidate scorecard within the ATS, schedules candidate interview as well as sending out calendar invitations to applicants.

San Francisco and London-based Robo Recruiter built a chatbot to keep potential candidates engaged and, in case the company's ATS allowed it, to keep their resumes updated at the same time. In addition, Robo Recruiter encourages the existing talent pool to apply to open jobs if the candidate were to confirm to the chatbot that they could be open for new jobs. As such, Robo Recruiter, through their smart chatbots, helps companies tap talent who have already stated their interest in joining the company.’s Talent Intelligence Platform (TIP) leverages Artificial Intelligence and Machine Learning to address the productivity loss facing enterprises from open/unfilled positions, wrong hires and employee attrition. has developed a comprehensive talent network unique to an organization by aggregating all internal and external data for an enterprise – from applicants to alumni – which is currently siloed across many different solutions. 's executive team has a cumulative pool of 80 patents and >6,000 research citations.

In Conclusion

As AI becomes more mainstream, and starts automating more menial, structured tasks, it will also contribute to enhancing tasks to be performed by humans.


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