Artificial Intelligence has become one of the most important technological forces reshaping modern Human Resource Management. Among different HR functions, talent acquisition and employee performance management are two areas where AI-based tools are being used widely for screening applications, shortlisting candidates, scheduling interviews, analysing skill gaps, predicting employee potential, monitoring performance indicators, and supporting managerial decision-making. The present paper examines the role of Artificial Intelligence in talent acquisition and employee performance management with special reference to emerging opportunities and organizational challenges. A descriptive cum analytical survey design was adopted for the study. A sample of 120 HR professionals and managers working in selected private-sector organizations was taken through purposive sampling. Data were collected with the help of a self-constructed structured questionnaire covering three areas: AI adoption in recruitment, AI use in performance management, and organizational challenges related to AI implementation. The reliability of the tool was found to be 0.84 through Cronbach’s alpha. Frequency, percentage, mean, and chi-square test were used for analysis. The findings revealed that the major opportunities of AI in talent acquisition were faster resume screening, reduction in manual workload, better candidate matching, improved recruitment planning, and data-based hiring decisions. In the area of performance management, AI helped in continuous feedback, identification of training needs, performance prediction, and objective tracking of employee contribution. At the same time, the major challenges were algorithmic bias, lack of transparency, data privacy concerns, high implementation cost, limited technical knowledge among HR staff, and employee fear regarding surveillance. The chi-square test confirmed a significant association between AI adoption and perceived improvement in talent acquisition, and also between AI-based performance management and perceived decision-making effectiveness. The paper concludes that AI can strengthen HR practices only when it is used as a supportive tool with human judgment, ethical governance, transparency, and employee trust.
Mansi Bhadoria, Rahul Kushwah· Journal of Management Studie...· 0 citations
Artificial Intelligence is rapidly changing the nature of Human Resource Management by making employee-related decisions more data-driven, timely, and analytical. Earlier HR practices mainly depended on manual records, supervisor judgment, employee surveys, and periodic review systems. In the present digital workplace, AI-supported tools are being used to understand employee engagement, predict dissatisfaction, analyse employee feedback, recommend learning opportunities, identify workplace concerns, and support managerial decision-making. The present paper examines the role of Artificial Intelligence in transforming employee engagement and decision-making in Human Resource Management. A descriptive cum analytical survey design was adopted for the study. A sample of 120 HR professionals, team leaders, and employees working in selected private-sector organizations was selected through purposive sampling. Data were collected with the help of a self-constructed structured questionnaire covering three areas: AI-supported employee engagement, AI-based HR decision-making, and organizational challenges in AI implementation. The reliability of the tool was found to be 0.85 through Cronbach’s alpha. Frequency, percentage, mean, and chi-square test were used for analysis. The findings revealed that AI contributes to employee engagement through real-time feedback systems, personalized learning suggestions, employee sentiment analysis, digital communication platforms, recognition tools, and predictive identification of disengagement. In HR decision-making, AI supports workforce planning, employee retention decisions, learning and development decisions, internal mobility, grievance analysis, and policy planning. However, the study also found important challenges such as data privacy concerns, employee fear of monitoring, lack of emotional understanding in AI systems, algorithmic bias, low trust, and overdependence on technology. The chi-square test confirmed a significant association between AI-supported engagement practices and perceived improvement in employee engagement. It also confirmed a significant association between AI-based analytics and effectiveness of HR decision-making. The paper concludes that AI can transform employee engagement and HR decision-making only when it is implemented with transparency, ethical safeguards, human supervision, and employee trust.
Mansi Bhadoria, Rahul Kushwah· Journal of Management Studie...· 0 citations
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