AI Powered Resume Screening System

Resume screening is the most time-intensive stage of recruitment, especially in large-scale hiring environments. Traditional manual evaluation often results in delays, inconsistency, and unintentional bias. With advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP), automated systems now offer reliable alternatives to manual screening. This paper presents an overview of an AI-powered resume screening system capable of parsing resumes, extracting key candidate information, comparing profiles with job descriptions, and generating ATS-based relevance scores. The system improves fairness, accuracy, and efficiency while reducing recruiter workload. The paper discusses system architecture, algorithms, advantages, limitations, and future scope of AI-driven recruitment.

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2025-12-05
DOI
https://doi.org/10.64388/irev9i6-1712632
Primary Topic
Expert finding and Q&A systems
Type
article
Field-Weighted Citation Impact
0.00
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AI Powered Resume Screening System

Iconic Research and Engineering Journals
Expert finding and Q&A systems
article

AI Powered Resume Screening System

article en

Abstract

Resume screening is the most time-intensive stage of recruitment, especially in large-scale hiring environments. Traditional manual evaluation often results in delays, inconsistency, and unintentional bias. With advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP), automated systems now offer reliable alternatives to manual screening. This paper presents an overview of an AI-powered resume screening system capable of parsing resumes, extracting key candidate information, comparing profiles with job descriptions, and generating ATS-based relevance scores. The system improves fairness, accuracy, and efficiency while reducing recruiter workload. The paper discusses system architecture, algorithms, advantages, limitations, and future scope of AI-driven recruitment.

Iconic Research and Engineering JournalsVol. 9(6)
Openalex Percentile: Top 48%
Expert finding and Q&A systems
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AI Powered Resume Screening System · Iconic Research and Engineering Journals (2025) | TGRS Research Map | TGRS