Published Paper Details:

Artificial Intelligence (AI) has emerged as a transformative force in contemporary organizations, fundamentally reshaping business processes, workforce practices, and operational strategies. The increasing integration of AI technologies, including machine learning, intelligent automation, predictive analytics, and data-driven decision-support systems, has significantly influenced how organizations manage resources, improve productivity, and achieve competitive advantage. Within India's rapidly expanding information technology sector, Pune has evolved as a major technology hub where organizations are actively investing in AI-driven solutions to enhance performance and operational effectiveness. The present study seeks to examine the impact of AI adoption on employee performance and organisational efficiency in the IT industries of Pune. While existing literature highlights the strategic benefits of AI, there remains limited empirical evidence regarding its measurable influence on workforce productivity and organizational outcomes within specific regional contexts. This research addresses this gap by investigating the extent to which AI adoption contributes to employee productivity, task efficiency, work quality, decision-making capability, and overall organizational effectiveness. The study adopts a mixed-methods research design that integrates quantitative and qualitative approaches. Quantitative data will be collected through structured questionnaires administered to employees and managers across selected IT organizations in Pune. Qualitative insights will be obtained through semi-structured interviews with industry professionals and organizational leaders. An AI Adoption Index will be developed to assess the degree of AI implementation based on factors such as automation intensity, AI tool integration, and organizational investment in AI technologies. Employee performance will be evaluated through indicators including productivity rate and task completion efficiency, while organizational efficiency will be measured using operational parameters such as process turnaround time, cost optimization, and resource utilization. Advanced statistical techniques, including correlation, regression, and mediation analysis, will be employed to examine the relationships among AI adoption, employee performance, and organizational efficiency. The study will also explore whether employee performance serves as a mediating factor between AI implementation and organizational outcomes. Furthermore, qualitative findings will provide deeper insights into employee perceptions, challenges, opportunities, and organizational readiness associated with AI adoption. The anticipated findings are expected to contribute to both academic and managerial knowledge by offering empirical evidence on the effectiveness of AI in enhancing organizational performance. The research will provide valuable recommendations for IT organizations, policymakers, and human resource professionals regarding sustainable AI integration, workforce development, and strategic decision-making. By focusing on Pune's IT ecosystem, the study will generate region-specific insights that can support organizations in maximizing the benefits of AI while addressing challenges related to employee adaptation, skill development, and organizational transformation. Ultimately, the research aims to advance understanding of how AI can be leveraged to achieve improved employee performance and greater organizational efficiency in a rapidly evolving digital environment.