Artificial Intelligence in Human Resource Management: Transforming Talent Acquisition and Workforce Analytics

The paper focuses on how Artificial Intelligence (AI) has revolutionized talent acquisition and workforce analytics within Human Resource Management (HRM). The research assesses the AI-based tools in enhancing the efficiency of recruitment, employee retention, and performance management. The mixed-methods approach was also used, which included both quantitative data gained through surveys and case studies, and qualitative data gained through the HR professionals. The AI efficacy in HR functions in terms of time-to-hire, accuracy of matching the candidates, and employee turnover was assessed using statistical analysis, machine learning algorithms, and qualitative coding techniques. The introduction of AI led to a 55% decrease in time-to-hire, a 20% rise in turnover prediction, and a 33% enhancement in engagement strategy performance. There was an increase in candidate matching accuracy (70% to 90%) and a reduction in employee turnover (40%). These findings indicate that AI would enable the optimization of HR functions, reduce operating costs, and improve decision-making. Recruitment and workforce analytics have been significantly made efficient, cost-effective, and decision-making with the use of AI in HR. However, there are also certain potential challenges in the study, such as the bias of the data collected and the need to implement models of ethical AI adoption. The AI is transforming the HR practices, but in future research, it is necessary to take into consideration the adaptive AI models, AI adoption framework, and integration of AI into the employee well-being in order to enhance the role of AI in HR