How AI Candidate Matching Improves Recruiter Productivity

Ai candidate matching

Recruiters face many challenges in their daily work. Sifting through hundreds of resumes for a single corporate job opening is one of their most monumental challenges. And the task becomes even more time-consuming for recruiters when each resume is given the attention it needs. That’s why recruiters need fast, accurate AI-powered tools, like candidate matching found in applicant tracking systems, to expedite hiring and stay productive and efficient.  

What is AI candidate matching? 

AI candidate matching is an intelligent recruiting tool that uses semantic search algorithms to match candidates with appropriate jobs. These semantic search algorithms go beyond looking at traditional keywords.  

Combined with artificial intelligence, AI candidate matching expands search capabilities like never before. But more than that, it allows recruiters to match candidates quickly and accurately. This ensures each candidate is placed in the right position, greatly shortening the candidate sourcing process
 

How does AI candidate matching work? 

Manual candidate matching is a tedious and time-consuming process that can lead to human error and costly mistakes. But AI candidate matching mitigates these risks.  

Combining algorithms and search criteria, this talent acquisition tool gives each applicant a ranking score based on pre-filled characteristics, priorities, and keywords, both specific and related. Ready to see it in action? Here’s how candidate matching works in four steps: 
 

  1. Custom selection parameters. Recruiters can select certain criteria, like experience, location, and salary requirements, to aid in their search.  
  2. Semantic search tools. Once parameters are selected, recruiters then use specific keywords to filter and match candidates. 
  3. Fast candidate submission. Candidate lists are then populated and organized, allowing recruiters to easily and quickly scan for the most valuable candidates.  
  4. Instantaneous communication. Finally, automated responses immediately notify candidates of their status.   

 

4 Ways AI Candidate Matching Improves Recruiter Productivity 

Automated recruiting solutions, like AI candidate matching, expedite the recruiting processes in significant ways and bolster recruiter productivity by an astounding 80%. Faster candidate matching helps recruiters make more placements, improving both hiring processes and bottom lines. But that’s only the beginning. 
 

1.Improve Time-to-Hire metrics 

One way AI candidate matching improves recruiter productivity is by reducing time-to-hire. Time-to-hire is the average number of days it takes a candidate to complete the hiring process. This includes the time an applicant spent applying for a position, all the way to their acceptance of the job.  

When combined with job mapping, AI candidate matching uses pre-determined keywords and semantic algorithms to match the best candidates with the best jobs the first time. This reduces time-to-hire by 40%, helping recruiters do their jobs even faster and more accurately than ever before. 
 

2.Reduce bias and diversify the recruiting process. 

AI candidate matching relies on data, parameters, and specific keywords to be effective. Because the process is automated and reliant on this data, candidate matching greatly reduces the risk of human bias. Other ways these innovative digital tools reduce bias include anonymous feedback options and demographic data visibility restrictions. 
 

3.Make data-driven decisions about recruiting processes

Digital tools and artificial intelligence are changing the way recruiters approach their work. By automating recruiting tasks, these AI powered recruiting tools are eliminating manual tasks, analyzing more data, and helping recruiters become more proactive. One way smart tools, like candidate matching, help improve proactivity is through the measurement of KPIs.  

KPIs (Key Performance Indicators), like time-to-hire and quality of hire, measure the accuracy and efficiency of your recruiting methods. Understanding these metrics gives recruiters better insight into what is working, or not working, in their recruiting processes. This allows them to make data-driven decisions when developing and enhancing recruiting strategies. 
 

4.Improve the likelihood that the right candidates are hired

The combination of human and machine capabilities allows recruiters to make faster, better decisions throughout the recruiting process. This reduces the chance of unsuccessful matches and increases the likelihood that the right candidates are placed in the right jobs.  

Utilizing custom algorithms, AI candidate matching takes the guesswork out of matching. Instead, data and analytics help ensure that only the most qualified candidates are matched, saving considerable time and energy for both candidates and recruiters.