The Impact of Artificial Intelligence on Business Models: Drivers of Value Capture

Artificial Intelligence (AI) is widely expected to strongly impact the way companies do their business. How firms use AI in practice to benefit from the technology is only slowly started to be examined in scientific literature. Especially the motivation for and drivers behind the AI application call for a detailed analysis. Building from the resource-based view and business model theory, the author proposes an update to current business model theory, when relating to an AI context. The results from the qualitative analysis of four company cases suggest that efficiency is not only a driver of value creation, like the classical theory suggests, but rather the central function and motivation to engage in AI activities to capture value. The focus of efficiencies is initially more attractive because they add higher value to the bottom line and are less complex to handle than customer experience-related activities. Thus, value capture through increased efficiency should be considered a stand-alone feature, unlike currently done. Further, the cases deliver first evidence that innovation of business models occurs mainly in terms of transaction content and transaction structure which can be related to a shift of focus on the following resources and capabilities: IT-infrastructure, data, talent, change management and culture. To optimally leverage AI technology and to eventually turn it into a long-term competitive advantage, the firm’s business model should offer solutions on how to achieve high values for these five drivers.