Automation and AI in Corporate Financial Management : adoption and strategic insights

Abstract

This thesis examines the adoption of automation and artificial intelligence (AI)-based tools in corporate financial management. The theoretical background is based on two theories. Firstly, to investigate the individual acceptance factors and their effects, the technology acceptance model (TAM) and its extended version TAM2 was chosen. Secondly, as the technology and its application in corporate financial management widens, there is a question of value creation enabled by these new tools. The second theory was resource-based view (RBV) which examines the internal capabilities and resources of a firm and tries to identify if they form a strategic competitive advantage. We found in our research of eight companies several interesting themes. For the TAM/TAM2 model, we found the actual acceptance factors mostly coincide well with the theory. The main factor we found was enhanced speed and accuracy which correspond well with the perceived usefulness factor of the TAM/TAM2 model. We also found that data and the internal resources of a company can indeed be a resource or a capability approaching a sustainable competitive advantage, in accordance with the RBV model.