Artificial Intelligence in Talent Acquisition and Employee Performance Management: Emerging Opportunities and Organizational Challenges
DOI:
https://doi.org/10.29121/ShodhPrabandhan.v3.i2.2026.116Keywords:
Artificial Intelligence, Talent Acquisition, Performance Management, Human Resource Management, Recruitment, Hr Analytics, Algorithmic Bias, Organizational Challenges, Employee PerformanceAbstract
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.
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