The rapid expansion of the Non-Banking Financial Company (NBFC) sector in India has intensified the demand for skilled and job ready employees, leading to increasing concerns regarding early employee attrition, particularly within the first year of employment. Many NBFCs continue to rely heavily on reactive hiring practices characterized by last minute recruitment, limited candidate engagement, and inadequate talent readiness mechanisms. Such practices contribute to mismatches between job expectations and employee preparedness, thereby increasing the likelihood of early exits. With advancements in recruitment technologies, Artificial Intelligence (AI) powered hiring tools and predictive analytics have emerged as effective mechanisms for improving candidate readiness, streamlining hiring processes, and predicting attrition risks.

This study aims to examine the transition from reactive to proactive hiring practices by leveraging AI powered talent readiness strategies to reduce early employee attrition in NBFCs. A quantitative research design is adopted using structured questionnaires administered to HR professionals and newly recruited employees across selected NBFCs. Data analysis techniques such as reliability testing, exploratory and confirmatory factor analysis, and Structural Equation Modelling (SEM) are proposed to examine relationships among reactive hiring, talent readiness, AI adoption, and early attrition outcomes