Use of Generative Artificial Intelligence in Business Models

The rapid advancement of Generative Artificial Intelligence, driven by Large Language Models such as ChatGPT, has received significant attention and generated extensive debate. Despite this growing interest, many organizations remain unprepared to adopt and scale AI technologies effectively. A lack of expertise and organizational capabilities often limits AI initiatives to conceptual discussions, preventing their integration into strategic business processes. This research adopts the Design Science Research methodology to address this challenge through three main stages: a systematic literature review, the development of a framework for integrating GenAI into business models, and validation through expert interviews. The findings reveal that existing research predominantly focuses on AI’s impact on internal processes and value creation, emphasizing automation, decision support, and enhanced engagement with customers and employees. However, less attention has been paid to AI's potential to enable entirely new products, services, and value propositions. To bridge this gap, this thesis introduces the AI-Enhanced Business Model Canvas, a framework that systematically embeds GenAI capabilities into the components of business models. This framework supports organizations in strategically leveraging AI to foster creativity, innovation, and sustainable value creation. The study contributes to the emerging body of knowledge at the intersection of GenAI and business models, providing both theoretical insights and practical guidance for organizations aiming to harness AI’s transformative potential.