Artificial Human Resource in MSME - Kumar, Abhineet (Digital Repository of Theses, 2025)
This dissertation explores the adoption, challenges, and benefits of artificial intelligence (AI)-powered Human Resource Management (HRM) tools within India's Micro, Small, and Medium Enterprises (MSMEs). Critical economic contributors, MSMEs face significant HR challenges due to limited resources, informal HR practices, and constrained technological adoption. AI-powered HRM tools present a promising solution to these challenges by automating processes, enhancing decision-making, and improving employee engagement. This study investigates these tools' acceptance levels, limitations, and advantages among MSME business owners and employees while addressing demographic and organizational influences. A mixed-methods research design was employed, combining quantitative data from a survey of 200 respondents and qualitative insights from focus groups. Quantitative findings reveal high acceptance levels, with over 70% of participants rating AI tools positively for their ease of use, efficiency, and recruitment capabilities. These tools demonstrated strong potential in enhancing recruitment efficiency, delivering personalized training programs, improving decision-making with predictive analytics, and reducing operational costs. However, the study identified critical limitations, including technical challenges, cost barriers, skill gaps, and privacy concerns. These barriers were more pronounced in micro and small enterprises, where resource constraints were most significant. Correlation analysis revealed interdependencies between these limitations, underscoring the need for holistic solutions such as cost-effective pricing models, targeted training programs, and robust data security measures. The findings emphasize the demographic trends in AI adoption, with younger professionals (aged 26-35) and employees in smaller enterprises showing the highest engagement. The study concludes that while AI-powered HRM tools offer transformative potential for MSMEs, addressing adoption barriers is essential for their widespread and practical use. By leveraging these tools strategically, MSMEs can enhance operational efficiency, workforce management, and long-term sustainability. This research provides valuable recommendations and lays a foundation for future studies exploring the integration of AI in HRM practices for MSMEs.