Artificial intelligence boundary resources: a relational view on leveraging “AI-as-a-Service”

In response to the increasing relevance of artificial intelligence (AI) for competitive advantage, firms can utilize the capabilities of AI-savvy partners via boundary resources. Due to AI facets, such as autonomy, inscrutability, and learning, this strategy holds substantial promises for productivity and innovation, yet is not free of risks, given the strategic importance of AI and potential dependencies in this key area. As the antecedents and consequences of this strategy are unclear, we build a theoretical framework about these aspects based on the relational view of competitive advantage. We test our hypotheses on a longitudinal dataset and find that internal AI knowledge and the presence of a chief information officer in the top management team are associated with selecting AI boundary resources for process improvements. High external market pressure exerted by digital ventures and the AI sophistication of industry peers are positively associated with selecting AI boundary resources for product improvements. We further find that the use of AI boundary resources for process improvements is positively associated with operational efficiency and the use of AI boundary resources for product improvements with increasing sales. We derive implications for IS research on managing AI and boundary resources, as well as managerial practice.