1. SAMI AWWAD AL-KHARABSHEH - Business Administration Department, Faculty of Business, Amman Arab University, Amman-Jordan.
Successful organizational operations in the competitive business world depend heavily on efficient Talent management. Employee turnover is increasing because traditional methods of developing and retaining talent frequently fall short of addressing the complexity of contemporary workforce dynamics. The main objective was to assess how artificial intelligence (AI) influences the relationship between TM and digital performance enhancement in Jordanian ICT companies. To gather the relevant data this study used a quantitative approach. The statistical population of the research comprised 180 senior managers from ICT companies in Jordan. The relevant information was gathered through the use of a standard questionnaire. To analyze the obtained model, Smart PLS version 4.07 software was used. The results showed that the incorporation of AI in TM strategies enhances the firm’s DP. This study adds to our understanding of the TM future, which is improved by AI to help businesses succeed and adapt in the digital age.
Talent Management (TM), Artificial Intelligence (AI), Talent Analytics (TA), Talent Acquisition (TAC), Succession Planning (SP), Performance Management (PM), Digital Performance (DP).