Artificial Intelligence Integration in Merging Financial and Human Resources Strategies: A Smart PLS-Based Empirical Study on Workforce Optimization with Special Reference to Delhi-NCR - Sharma, Vasudha; Chaudhary, Amita; Priyanka; Kumari, Saroj; Mansi; Mehrotra, Salabh (Journal of Neonatal Surgery, 2025)
Aim/Objective: This paper governs artificial intelligence integration in merging financial and HR strategies in Delhi-NCR, to optimize workforce performance within organizations in Delhi-NCR. Methodology/Approach: The paper usages Partial Least Square-Structure Equation Modelling (PLS-SEM) to analyse data collected from 407 respondents using convenience sampling. Key independent variables comprise AI Integration in HR and Finance, Resource Allocation, Financial Performance, Employee Performance Metrics, and dependent variable in this study is workforce optimization. Findings: The results reveal a significant positive relationship between AI integration in HR and finance and workforce optimization. Each independent variable demonstrated a notable positive impact on workforce optimization, with AI integration in HR and finance showing the strongest influence. Originality/Value: To optimize workforce management, this study highlights importance of implementing AI-driven strategies that integrate HR and financial insights. Organizations in Delhi-NCR are encouraged to force AI for better resource allocation and data-driven performance monitoring to enhance productivity. Limitations and Recommendations: The study is limited to 407 sample size. This study employs convenience sampling which diminishes the generalizability of findings to wider population. Future research can be showed with longitudinal research design and more different sampling methods with larger sample size.