TY - THES A1 - Andrade Moncayo, Mathias Esteban T1 - Enterprise value creation through artificial intelligence BT - a conceptual framework for managing generative AI application projects N2 - The rapid expansion and adoption of generative AI technologies are revolutionizing various industries, significantly impacting business operations, innovation, and customer engagement. This bachelor thesis explores the integration of generative AI in enterprise environments, focusing on the development of a conceptual framework to guide AI implementation and management. The study begins by analyzing the current market trends and the exponential growth of generative AI, projected to reach €333.70 billion by 2030. It then delves into the potential benefits of generative AI, including enhanced productivity, personalized customer experiences, and accelerated innovation cycles. Despite these advantages, the study identifies several challenges, such as the risk of IT project failures due to incomplete requirements, lack of user involvement, and shifting project objectives. The research is structured around four key phases: The Strategic Insight and Evaluation Phase, The Domain-Specific Fine-Tuning Phase, The Adoption and Adaptation Phase, and The Iterative DDS Coordination Process. Each phase addresses specific aspects of AI integration, from initial strategic planning to ongoing refinement and collaboration between business and technical teams. By conducting a thorough literature review and incorporating insights from a survey of 30 industry professionals, the study provides a comprehensive understanding of the practical and theoretical implications of generative AI. The findings highlight the importance of aligning AI initiatives with strategic business goals, customizing AI models to specific domains, and fostering organizational readiness for AI adoption. The thesis concludes by offering recommendations for future research, emphasizing the need for empirical validation of the conceptual framework, large-scale surveys, and longitudinal studies to explore the long-term impacts of AI integration. By addressing these areas, future research can further enhance the effectiveness and sustainability of generative AI in enterprise environments. Y1 - 2024 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-51512 CY - Ingolstadt ER -