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.

With business ecosystems digitalizing by the force of digital innovation, the deployment of boundary resources (such as application programming interfaces: APIs) becomes a strategic option across contexts. We distinguish between boundary resources that provide access openness and those that provide resource openness, and theorize the antecedents and consequences of their deployment. Employing panel data regressions to a longitudinal cross-industry dataset, we find that the digital knowledge base of the focal firm and the existence of potential digital complementors drive boundary resource deployment. Such deployment benefits firm performance depending on the firm’s market power. From our empirical analysis, we reveal a differentiated perspective on the quality of the confined openness provided by boundary resources as well as the embeddedness of their deployment in the rationales and motivations of the associated actors in digital business ecosystems. We complement the existent theoretical framework on boundary resources and provide valuable insights to managers reflecting about deploying boundary resources in a beneficial way.

Aiming to support digital innovation endeavours, industrial-age companies increasingly acquire firms that heavily build upon digital technologies. Related research has raised serious concerns regarding the prospects of such plans, yet has not focused the particular context of digital mergers and acquisitions (M&A). Drawing on a knowledge-based perspective as well as the particularities of digital technologies and the context of digital innovation, we theorise the link between digital M&A, a digital knowledge base on the part of the acquirer, and the consequences for digital innovation and firm performance. We employ panel data regressions to a longitudinal dataset of the world’s largest automobile manufacturers. Our findings suggest that executing digital M&A contributes to building the digital knowledge base of industrial-age firms, which in turn enables them to drive digital innovation. Our findings further indicate that digital innovation improves firm performance of industrial-age firms. We discuss implications for information systems research about M&A and digital innovation as well as recommendations for managerial practice.