The Impact of Artificial Intelligence Applications on The Effectiveness of Recruitment and Selection processes on Telecommunication Enterprises | ||||
المجلة العلمية للدراسات التجارية والبيئية | ||||
Volume 16, Issue 2, April 2025, Page 2631-2672 PDF (1.11 MB) | ||||
Document Type: المقالة الأصلية | ||||
DOI: 10.21608/jces.2025.437266 | ||||
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Authors | ||||
Ahmed Abdel Sadek* ; Ahmed Bahgat El Seddawy* ; Nancy M. Rizk* | ||||
College of Management and Technology – AASTMT | ||||
Abstract | ||||
The application of Artificial Intelligence (AI) in recruitment and selection has transformed talent acquisition, especially within telecommunication companies where the need for skilled workers is ever-increasing. AI empowers enterprises to improve their recruitment procedures' efficiency and equity. This study aimed to examine the impact of (AI) applications on the effectiveness of the recruitment and selection process on telecommunication enterprises in the Arab Republic of Egypt. The study focused on four key dimensions of AI applications: Expert Systems, Big Data Analytics, Chatbots, and Machine Learning. A quantitative approach was adopted, utilizing a questionnaire distributed to a sample of 240 individuals working in the human resources sector within telecommunications companies. The statistical analysis revealed a significant and positive impact of all these dimensions on enhancing the efficiency and effectiveness of recruitment and selection processes. The results demonstrate that AI technology improves the traditional recruitment process and enables data-driven hiring decisions that improve personnel quality. Expert systems provide organized insights, big data analytics discover patterns and candidate behaviors, chatbots improve interactions, and machine learning optimizes selection criteria based on anticipated performance and supporting managerial decision-making and improving the quality of human capital outcomes in the telecommunications sector | ||||
Keywords | ||||
Artificial Intelligence; Human Resource Management; Natural Language Processing; Human Computer Interaction; Optical Character Recognition | ||||
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