DIGITAL TRANSFORMATION IN HR: AUTOMATING AND ENHANCING RECRUITMENT PROCESSES

Abstract

Despite the rapid technological change in society, technological progress in recruitment specifically, until now, many human resource departments still heavily rely on manual processes such as candidates’ resume screening, scheduling an interview, and assessing the candidates. Thus, the mentioned inefficiencies result in higher recruitment costs, increased hiring timelines, and decreased candidate satisfaction. All of this, in turn, negatively impacts the company’s reputation, brand image, and ability to attract top talent. This paper aims to address these challenges by developing an AI-powered applicant tracking system (ATS) to automate and optimize key recruitment process functions. The main objective of the paper is to evaluate how the use of AI technologies in the recruitment platform can improve essential hiring metrics, specifically metrics such as time-to-hire, cost-per-hire, and time-to-fill. A secondary objective of the paper is to research deeper global HR challenges and present inefficiencies in the process, together with identifying how AI-based methods can resolve them through automation and data analysis. The efficiency of the AI-supported ATS platform was tested in the context of medium and large enterprises. Key findings after implementation indicated a significant reduction in essential metrics such as time-to-hire (measured in days), a notable decrease in cost-per-hire (measured in tenge), and improved efficiency in time-to-fill (measured in minutes). The above-mentioned results show the potential and the ability of the platform to optimize processes connected with recruitment, operational inefficiencies, and hiring the right candidates. Overall, the study demonstrates the value of integrating AI technologies into recruitment systems to successfully meet modern HR demands with greater speed, accuracy, and scalability.