The contemporary global economic landscape is undergoing profound transformations characterized by rapid technological advancements, shifting labor market demands, and unpredictable macroeconomic fluctuations. For emerging economies with substantial demographic dividends, such as India, the intersection of these changing employment patterns and youth unemployment presents a critical socioeconomic challenge. This paper explores the multidimensional causes and economic consequences of unemployment among Indian youth, contextualizing the issue within both traditional macroeconomic theories and novel technological paradigms. While historical analyses of employment have largely focused on the Keynesian dimensions of capital growth and aggregate demand, modern labor markets are increasingly dictated by algorithmic mediation, artificial intelligence exposure, and complex geographic mobility. Consequently, traditional explanations of structural and frictional unemployment are no longer sufficient to capture the realities faced by young job seekers.  In this study, we propose a comprehensive theoretical and methodological framework to evaluate the changing patterns of employment and their direct impact on the economic well-being of young workers. Drawing on international evidence regarding migration-induced unemployment, the systemic failures of youth-employment policies in developing contexts, and the emerging concept of Artificial Frictional Unemployment (AFU), we contextualize these phenomena for the Indian labor market. The paper systematically categorizes the literature into macroeconomic dynamics, technological disruptions, and policy implementation challenges. We observe that while growth models can explain long-term trends and cyclical fluctuations, the micro-level realities of youth unemployment are heavily influenced by emerging algorithmic barriers in recruitment and varying degrees of AI exposure across different occupational sectors.  To address the gaps in existing empirical analyses, we introduce a structured, multi-tiered methodological approach designed to assess both macro-level labor market efficiencies and micro-level technological frictions. This proposed framework utilizes a blend of econometric modeling of the Beveridgean unemployment gap and the simulation of automated recruitment systems to quantify the true extent of artificial barriers facing young applicants. Furthermore, the paper rigorously discusses the practical implications of these shifting paradigms, highlighting the urgent need for labor market infrastructure reform and improved policy coordination. We also detail the inherent limitations of the proposed approach, including challenges related to informal sector data sparsity and the potential failure modes of predictive algorithms. Ultimately, this research provides a vital theoretical foundation and an actionable evaluation plan for policymakers and economists seeking to mitigate youth unemployment and harness the economic potential of India's younger generation in an increasingly automated world.