Year: 2025
Type: article
Abstract: In the competitive landscape of recruitment, organizations face significant challenges in efficiently screening resumes to identify the most suitable candidates. Traditional resume screening methods are often labor-intensive and prone to human error, leading to biases and inefficiencies. This paper presents a Smart Application Tracking System (ATS) that leverages Generative Artificial Intelligence (Gen AI) and advanced Natural Language Processing (NLP) techniques to automate and enhance the resume screening process. The proposed system analyzes resumes in real-time, matching them against job descriptions to provide a comprehensive evaluation of candidate qualifications. By employing semantic analysis and contextual understanding, the Smart ATS improves the accuracy of candidate selection while significantly reducing the time and effort required for manual screening. Evaluation metrics, including precision, recall, and F1-score, demonstrate that the Smart ATS outperforms traditional methods, effectively identifying qualified candidates and minimizing biases. The integration of Gen AI not only streamlines the recruitment process but also promotes fairness and transparency in hiring practices. This innovative approach has the potential to transform the recruitment landscape, enabling organizations to make more informed hiring decisions and ultimately leading to better workforce outcomes.
Authors: Venkata Anitha Varikallu, Raheeman Shaik, P. Pardasaradhi
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: gold
OpenAlex ID: W4410405367