Citation :

Tasriqul Islam, Sadia Afrin, Neda Zand, 2023. "Forecasting the Future Job Market: Leveraging AI and Predictive Analytics to Revolutionize Talent Acquisition Strategies" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 1, Issue 2: 50-62.

Abstract :

In today's competitive and fast-changing business environment, organizations must rethink their quantitative talent decisions. HRM has been disrupted by Big Data and AI. Business executives today have unparalleled access to management and large-scale talent data, enabling data science study into organizational behavior. They can then make better real-time judgments and adopt more effective personnel management techniques. Talent analytics has been a viable topic of applied data science for HRM in the previous decade because of AI communities and several research programs. Thus, we present a current and comprehensive review of HRM talent analytics AI technology's rapid progress is affecting several sectors, including talent recruiting. This study examines how AI-powered tools are changing recruiting, evaluation, and hiring procedures. Considering increased global competition for top talent, data-driven recruitment strategies are essential. Machine learning, predictive analytics, and natural language processing are key AI technologies for improving candidate experiences and recruiting faster. These technologies are needed to filter resumes, match prospects, and schedule interviews. To clarify, we start by explaining talent analytics and identifying pertinent data. Next, we give a detailed taxonomy of relevant research endeavors, grouped into three categories based on three application-driven scenarios: talent management, organization management, and labor market analysis. Finally, we assess AI-driven talent analytics and identify topics for further research.

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Keywords :

AI, Recruiting, Technology, Organizational Management, Labor Market Analysis.