Momina Humayun2025-09-282025-09-282024https://escholar.umt.edu.pk/handle/123456789/7263This study investigates the interplay between artificial intelligence (AI), technological adoption, and economic variables, focusing on their implications for unemployment and economic growth. Employing the Autoregressive Distributed Lag (ARDL) and Dynamic Ordinary Least Squares (DOLS) methodologies, the study examines macroeconomic data to uncover long-term determinants of unemployment. AI and machine learning (ML) adoption demonstrate a positive association with reduced unemployment, reflecting their potential to generate new job opportunities. Conversely, increased digitization through data science (DS) correlates with decreased unemployment, underscoring the importance of digital skills in modern economies. The key insights of this study shed light on the perspectives to existing literature, revealing complex interactions between AI adoption, economic growth, and labor markets. While supporting traditional economic theories on technological impacts, such as skill-based technological change (SBTC), the findings also challenge some prevailing notions. Overall, this research underscores the multifaceted nature of AI's economic impact, emphasizing the outcomes of the labor market in the developing countries. It further suggests some more avenues for future research by considering dynamics of technological adoption and economic outcomesenThesis