Global Engineering Solutions Review

Abstract

This research examines the revolutionizing effect of Artificial Intelligence (AI) on talent management, with emphasis on AI-driven recruitment and its effect on talent acquisition. AI-driven recruitment applies predictive analytics and automated resume screening to improve talent acquisition and match job requirements with candidate abilities. AI is also used in employee retention, where predictive modeling detects risk of turnover and customized development plans. The study employed a qualitative exploratory approach, where semi-structured interviews were administered to 10 respondents with direct exposure to AI-enabled hiring tools. Thematic analysis was employed to examine data via interviews, centered on the role of AI in recruitment efficiency, AI implementation in recruitment, constraints, and implications in the future. The study seeks to shed light on major insights into AI's function in talent management. Findings investigated that AI has hugely impacted the candidate screening and shortlisting process, minimizing the workload and enabling strategic hiring decisions. AI-driven ATS screens resumes, ranks candidates against job-fit scores, and pushes top talent forward within minutes. This has reduced the workload and enabled HR to concentrate on strategic hiring decisions. AI has also enhanced the accuracy of recruitment by assessing the thinking ability, personality, and cultural alignment of candidates. AI-based recruitment eliminates prejudice, automates routine tasks, and enhances diversity and inclusion by minimizing unconscious bias. Nevertheless, AI suffers from algorithmic bias, fairness and inclusion challenges, and a lack of capability to properly assess soft skills. These shortcomings render HR highly reliant on human judgment for recruitment decisions.