Leveraging “AI-as-a-Service” – Antecedents and Consequences of Using Artificial Intelligence Boundary Resources

Increased data availability and computing power allows businesses across industries to employ AI technologies in their products and processes. Yet, leveraging AI effectively requires high investments. To reduce these investments, companies can implement AI capabilities directly via boundary resources such as application programming interfaces (APIs). However, research tells us little about antecedents and performance consequences of the use of AI boundary resources. To close this gap, we derive hypotheses from the resource-based view and the relational view of competitive advantages and test these hypotheses on a panel dataset of S&P 500 firms for the years 2010 to 2018. Our results show that firms with high levels of internal AI capabilities are particularly likely to adopt AI boundary resources for process improvements; firms with high external market pressure are positively associated to use AI boundary resources for customer solutions; and the use of AI boundary resources has a positive performance effect.