Recent years have seen a reemergence of interest in artificial intelligence (AI) among both managers and academics. Driven by technological advances and public interest, AI is considered by some as an unprecedented revolutionary technology with the potential to transform humanity. But, at this stage, managers are left with little empirical advice on how to prepare and use AI in their firm’s operations. Based on case studies and the results of two global surveys among senior managers across industries, this article shows that AI is typically implemented and used with other advanced digital technologies in firms’ digital transformation projects. The digital transformation projects in which AI is deployed are mostly in support of firms’ existing businesses, thereby demystifying some of the transformative claims made about AI. This article then presents a framework for successfully implementing AI in the context of digital transformation, offering specific guidance in the areas of data, intelligence, being grounded, integrated, teaming, agility, and leadership.

Machine-age technologies, including automation, robotics, and artificial intelligence, are profoundly expanding the variety of service interfaces and therefore the possible ways that customers and firms can interact across customer journeys. This expansion challenges service firms’ capabilities to deliver coherent streams of interactions for effective customer engagement. This article develops a conceptual framework of firm capabilities that enable firms to operate with “one voice” to deliver seamless, harmonious, and reliable interactions across diverse interfaces in a customer journey. The proposed framework integrates three themes: (1) service interaction space to capture the interrelationship among devices, interfaces, interactions, and journeys; (2) learning and coordination as core capabilities for generating and using intelligence, respectively, to enhance customer engagement in subsequent interactions; and (3) one-voice strategy to configure learning and coordination capabilities in combinations that meet conditions of fitness and equifinality for effective customer engagement. We provide several research questions and priorities to guide research and practice.

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Statistical power is the probability of accepting the null hypothesis when it is false (type II error). This research note reports the results of a statistical power analysis of international business research published in the Journal of International Business Studies, Management International Review, the Academy of Management Journal, and the Strategic Management Journal from 1990 to 1999. The results show that, although average statistical power is high compared with other disciplines, it is sufficient only for large effect sizes (ESs). Only studies published in the Journal of International Business Studies and the Academy of Management Journal achieve average statistical power levels that are sufficient for both medium and large ESs. Still the observed likelihood of committing type II errors in international business research is very high for small ESs (92%) and high for medium ESs (45%). In addition, statistical power is not explicitly mentioned or used by international business researchers, a weakness that this note is designed to change. Journal of International Business Studies (2003) 34, 90–99. doi:10.1057/palgrave.jibs.8400006