Open Access

Abdul Hadi

• This thesis explores the transformative impact of Artificial Intelligence (AI) on capital market efficiency and investor behavior, with a comparative lens on developed and emerging markets. It investigates how AI technologies—such as machine learning, robo-advisors, and algorithmic trading—are reshaping investment strategies, reducing behavioral biases, and influencing market dynamics. The study integrates theoretical frameworks, including the Efficient Market Hypothesis, Behavioral Finance, and the Adaptive Markets Hypothesis, to contextualize AI’s role in modern finance. A mixed-methods approach combines literature review, empirical analysis, and survey data from Germany, India, and Pakistan to assess regional disparities in AI adoption, trust, and effectiveness. Findings reveal that while AI enhances decision-making and market efficiency, its benefits are unevenly distributed due to infrastructural, regulatory, and digital literacy gaps. German investors exhibit higher trust and adoption rates, leading to more efficient and diversified investment behavior, whereas emerging markets face barriers such as limited access and awareness. The thesis concludes with policy recommendations to foster inclusive AI integration and outlines future research directions to bridge the digital divide in global financial systems