| dc.description.abstract | Artificial intelligence (AI) is a technology that uses machine-based intelligence and advanced computing to mimic human cognitive functions to build, create, develop, make decisions, and perform tasks on its own (Jingyu Li. et al., 2021). Prior literature has espoused a wide variety of AI use capabilities, but there is a lack of research on AI outcome factors and its influence on organizational outcomes. This dissertation aims to help fill these research gaps by examining the aspects of managing AI and its outcomes through two studies. Study 1 examined the influence of perceived risks, controls, and AI connectedness on AI outcomes. I conducted a confirmatory factor analysis and a partial least squares structural equation modeling (PLS-SEM) analysis. The results indicated AI connectedness is an influential mediator and that manual controls have a significant positive influence on AI connectedness. Study 2 reviewed how AI outcomes influence competitive intelligence and organizational outcomes, with strategy orientation and reactionary strategy being moderators of the relationships. Using PLS-SEM analysis methods, results showed that competitive intelligence is a significant mediator between AI outcomes and organizational outcomes and strategic factors have significant main effects on competitive intelligence. Findings from these studies contribute to academic literature by illustrating the key role of AI controls and AI connectedness in influencing AI outcomes. Further, this dissertation also shows that improvements in AI outcomes can subsequently lead to improved organizational outcomes through competitive intelligence. These findings have important practical significance since managers can leverage AI controls and strategic focus to improve AI outcomes and organizational outcomes. | en_US |
