AI Based E-Recruitment System

Abstract

Modern web-based e-recruitment methods have revolutionised advertising, source tracking, and online inquiry forms with the associated start-up and maintenance costs. Attracting and hiring qualified candidates, navigating online recruiting tools, increasing unsuitable applications, and discrimination and diversity issues are just a few of the drawbacks of e-recruitment. A platform with AI algorithms is developed to overcome limitations, especially for Saudi private and public sector recruiters who lack AI in their application processes. The Unified Theory of Acceptance and Use of Technology (UTAT) measured user acceptance of e-recruitment systems, with a Cronbach's alpha of 0.96 indicating high reliability. The platform and its features were evaluated using five-point Likert scales, with mean responses exceeding 3.4, indicating high acceptability. This PhD developed the Artificial Intelligent Recruitment (AIRec) platform, ranking candidates with 99 per cent accuracy. Improve corporate image and profile, reduce recruitment and overhead costs, use better tools to select candidates based on sound criteria, provide tracking for both candidates and employers. AIRec also aims to change HR and line management culture and behaviour. The platform and its contributions were tested in real-world scenarios in the top Saudi government and university recruiting bodies. Based on Cronbach's alpha testing and validation, the result was 0.97 out of 1. The results show the system's high reliability.