Research on the Application Effect of Artificial Intelligence in Enterprise Talent Screening

DOI

10.2991/978-94-6463-742-7_16How to use a DOI?

Keywords

Resume screening; Deep learning; BERT; Human resource management; Recruitment automation

Abstract

While artificial intelligence has shown promise in recruitment, existing research lacks comprehensive empirical evidence comparing AI-powered and manual resume screening in real enterprise settings. This study addresses this gap through a novel controlled experiment using 1,000 technical position resumes from a leading Internet company, introducing three key innovations. First, we develop an advanced hybrid screening model that uniquely integrates BERT-based semantic analysis with domain-specific feature engineering, specifically designed for technical position evaluation. Second, we propose a multi-dimensional evaluation framework that systematically assesses screening performance across efficiency, accuracy, and cost dimensions - an approach not previously applied in AI recruitment studies. Third, we conduct the first large-scale comparative analysis of AI versus human screening performance under identical conditions, providing empirical evidence for the practical implications of AI adoption in recruitment. Results demonstrate significant improvements over existing approaches: our hybrid model reduces processing time from 180 to 2.5 s per resume while achieving 92% accuracy, a 4% improvement over manual screening. The system’s operating costs are 75% lower than traditional methods, while maintaining consistent evaluation standards across large volumes. Unlike previous studies that focused primarily on accuracy metrics, our comprehensive evaluation framework reveals the synergistic benefits of AI-human collaboration in recruitment. These findings provide novel insights for organizations considering AI recruitment tools, suggesting that optimal results are achieved through a balanced integration of AI efficiency and human expertise in the screening process.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yongqiang Xiao
AU  - Zenghua Zhang
AU  - Zhengkai Guo
PY  - 2025
DA  - 2025/05/31
TI  - Research on the Application Effect of Artificial Intelligence in Enterprise Talent Screening
BT  - Proceedings of the 2025 4th International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2025)
PB  - Atlantis Press
SP  - 132
EP  - 141
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-742-7_16
DO  - 10.2991/978-94-6463-742-7_16
ID  - Xiao2025
ER  -