Type: article
Abstract: Digital transformation has increased competitive pressure and made technology investment decisions more complex and strategically relevant. While IT investments have traditionally been evaluated using established financial metrics, artificial intelligence (AI) changes the underlying logic of investment decisions. AI systems are characterized as a bundle of heterogeneous capabilities, making it difficult to predict their performance prior to implementation. Moreover, realizing AI value typically depends on complementary organizational changes, such as process redesign and new decision routines, meaning that benefits emerge dynamically over time rather than being immediately observable. These characteristics challenge traditional investment appraisal approaches and suggest that different decision criteria may become more influential in AI contexts. Against this background, it remains unclear which attributes drive managerial preferences when allocating resources to AI technologies. This study addresses this question using a discrete choice experiment with a split-sample design to compare AI and BI investment scenarios.
Author: Santos Gabriel, Victoria Sofia
Institution: University of Bamberg
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7222992787