Conference Agenda

Generative Artificial Intelligence (GenAI) has taken society by storm in recent years, with comparisons drawn to past industrial revolutions in the literature in terms of disruptive potential. Innovations like GenAI force businesses to transform their business models to remain competitive. Literature connecting AI and business model innovation (BMI) is limited but emerging; specifically, GenAI's ability to shape future business models has not been studied at an industry level. Banking warrants focused attention given it has been at the forefront of digital innovation, its diverse service types across multiple customer segments, and the significant information asymmetries that GenAI could address. This paper explores BMI in banking through a GenAI lens, conducting a structured literature review of GenAI applications, followed by a hybrid thematic analysis. We contribute to theory by combining value chain analysis with BMI frameworks, creating an integrated analytical approach for studying technological disruption. We identify 28 distinct applications across 40 articles, mapping them to the banking value chain and outlining six levers through which BMI could be delivered in banking. Our study presents methodologies replicable for other industries and identifies avenues for future research.