artificial intelligence in the data economy: a conceptual and thematic review of business model transformations

This study presents a conceptual and thematic review of how artificial intelligence (ai) transforms business models within the data-driven economy. drawing on a structured four-phase methodology—comprising conceptual framing, systematic literature selection, thematic analysis, and framework development—the research synthesizes insights from peer-reviewed sources published between 2015 and 2025. the findings reveal three dominant dimensions of ai-enabled transformation: technological enablement, data-driven value creation, and organizational reconfiguration. ai technologies such as machine learning, natural language processing, and intelligent automation are shown to enhance operational efficiency, strategic agility, and sustainability outcomes across sectors including education, manufacturing, and urban infrastructure. despite its transformative potential, the literature reveals gaps in longitudinal analysis, trust dynamics, and the integration of ai with circular economy principles. the study proposes a multi-dimensional conceptual framework grounded in general-purpose technology theory, schumpeterian innovation, and systems thinking. practical implications highlight the need for strategic alignment, capability development, and cross-sector collaboration to optimize ai adoption. this review contributes to the academic discourse by clarifying the systemic role of ai in business model innovation and identifying pathways for future empirical research and managerial application.