A Study on AI-Driven Recruitment and Selection Practices with Special Reference to Bangalore District

The rapid advancement of artificial intelligence (AI) has significantly transformed recruitment and selection processes, particularly in technology-intensive organizational environments. AIdriven recruitment systems are increasingly employed to automate résumé screening, enhance candidate matching, and improve hiring efficiency. Despite their growing adoption, empirical evidence examining their effectiveness and implementation challenges within emerging economy contexts remains limited. This study investigates AI-driven recruitment and selection practices with special reference to Bangalore District, a major hub for technology-driven organizations in India. The study adopts a descriptive and analytical research design based on primary data collected from 300 HR professionals working in organizations that actively use AI-enabled recruitment tools. Data were gathered through a structured questionnaire and analyzed using statistical techniques such as descriptive statistics, correlation analysis, chisquare test, and paired sample t-test. The results reveal a high level of adoption of AI-driven recruitment practices among Bangalore-based organizations, with significant improvements observed in recruitment efficiency and candidate quality following AI adoption. Correlation analysis indicates strong positive relationships between AI adoption, perceived effectiveness, and recruitment efficiency, while the paired sample t-test confirms statistically significant improvements in recruitment outcomes after AI implementation. However, the findings also highlight persistent challenges related to implementation cost, algorithmic bias, and the availability of skilled HR analytics professionals. The study concludes that while AI-driven recruitment systems deliver measurable operational benefits, their successful deployment requires robust governance mechanisms, ethical oversight, and continuous capability development. The study contributes region-specific empirical evidence to the literature on AI in human resource management and offers practical insights for organizations seeking to implement responsible and effective AI-driven recruitment strategies.