AI Adoption and System-Wide Change
19 Pages Posted: 12 May 2021 Last revised: 8 Mar 2023
Date Written: November 9, 2022
Analyses of AI adoption focus on its adoption at the individual task level. What has received significantly less attention is how AI adoption is shaped by the fact that organizations are composed of many interacting tasks. AI adoption may, therefore, require system-wide change which is both a constraint and an opportunity. We provide the first formal analysis where multiple tasks may be part of a loosely or strongly coupled system. We find that reliance on AI, a prediction tool, increases decision variation which, in turn, raises challenges if decisions across the organization interact. Loose coupling by reducing inter-dependencies between decisions softens that impact and can facilitate AI adoption. However, it does this at the expense of synergies. By contrast, when there are mechanisms for inter-decision coordination, AI adoption is enhanced in a tightly coupled environment. Consequently, we show that there are important cases where AI adoption will be enhanced when it can be adopted beyond tasks but as part of a designed organizational system.
Keywords: artificial intelligence, machine learning, prediction, systems
JEL Classification: O32, L23
Suggested Citation: Suggested Citation