International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI powered Recruitment System

Author(s) Mr. Pranay Sharma, Mr. Prashant Khanal, Mr. Saurav Battu, Mr. Soumya Chakrabarty, Prof. Harvendra Kumar Patel
Country India
Abstract This paper discusses findings from a study exploring an integrated recruitment system designed to address fragmentation in high-volume hiring. Contemporary recruitment relies on disconnected tools—resume screening through one platform, interviews through another, tracking on yet another—creating data silos and inconsistent evaluation standards. We propose an approach that unifies resume parsing, candidate matching, and interview assessment within a single pipeline incorporating explainability mechanisms. The system was evaluated using 1,000 anonymized resumes from a mid-sized technology company. The results showed an 18 percent improvement in ranking precision, revealed a previously unnoticed candidate segment (15 percent of applicants) with a 35 percent conversion rate to offers, decreased processing time from 15 minutes to 4 seconds per candidate, and increased recruiter confidence in algorithmic recommendations by 40 percent when transparent reasoning was provided. These results imply that system integration, when combined with explainability, can simultaneously improve recruitment efficiency and reduce systematic bias.
Keywords Algorithmic fairness, Natural Language Processing, Explainable AI, Applicant Tracking Systems, Recruitment Automation
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-25
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.64134
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E-ISSN 2582-2160
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