Gen-AI’s effects on new value propositions in business model innovation: Evidence from information technology industry

Generative AI (Gen-AI) with its evolving natural language capabilities is dramatically changing the way that businesses operate and customers consume their products and services. While existing literature discusses Gen-AI’s impact on computer science and engineering, its adoption significantly influences business models across various industries. This paper focuses on how Gen-AI affects new value propositions within business model innovation (BMI). The qualitative research method is adopted in this research. The data is collected and analyzed through 32 semi-structured interviews and archival sources. The study identifies five approaches — knowledge querying-based cloud solutions, content creation, AI agents, foundation models, and upstream industry chain infrastructure — that Gen-AI affects new value propositions in BMI. This research introduces empirical evidence from the information technology (IT) industry, broadening the contextual boundaries of Gen-AI’s new value propositions in BMI. The study advances beyond isolated mechanisms, providing a quadrant view and process map to illustrate the interrelated dynamic effects of Gen-AI’s new value propositions in both radical and incremental BMI. • Gen-AI enables five new value propositions for BMI in IT industry. • Impacts include unified upstream infrastructure and customized downstream solutions. • AI agents and AI generated content detectors are radical BMI; others incremental. • A process model maps Gen-AI’s value propositions for incremental and radical BMI. • Foundation models enable various BMI but rely on upstream support.