Third-generation hiring systems are set to remove the inefficiencies faced in the current candidate screening processes by intelligently understanding the context in candidate resumes by leveraging the capabilities of AI.
Introducing The Third-Generation Hiring Systems
The third-generation hiring systems enable intelligent candidate searching made possible due to a combination of artificially intelligent searching and matching engines. It helps rank candidates using information retrieval, NLP, contextual intelligence, and data mining. This enables recruiters to find the best candidates even from a vast talent pool or if the candidate’s resumes are not keyword-optimized.
Comparing The Third-Generation Hiring Systems With Its Predecessors
To understand how the third generation of hiring systems is different from previous generations, we will have to look at three key metrics related to candidate hiring.
Understanding How Third-Generation Hiring Systems Work
Imagine a candidate not having an optimized resume. The resume doesn’t have the keywords related to the job description or having ambiguous keywords. For example, suppose there is a vacancy with the job title “editor,” which can have different meanings related to the job context. It can mean a video editor or an online article/blog editor. With traditional tools, it can so happen that a video editor’s CV might rank on top of a blog editor due to keyword use, even if the job vacancy is for the latter candidate. The deserving candidate might get screened out in the first phase itself. However, with AI, you can be assured that the right-fit candidates are screened, helping save time, money, and resources and also guaranteeing a high-quality hire. The AI algorithms can understand the context throughout the data in the resume to correctly identify an online blog editor, ensuring that recruiters are exposed to the right talent.