Harnessing AI-Powered Data Capabilities for Outside-In Marketing: A Qualitative Exploration

As firms increasingly deploy artificial intelligence (AI) to navigate complex market environments, understanding how AI-powered data capabilities shape outside-in marketing processes has become theoretically consequential. Employing a qualitative design with in-depth interviews across diverse industries, organizational sizes, and geographic contexts, this study addresses the knowledge gap. Grounded on the Resource-Based View, Dynamic Capabilities perspective, and Relational View, we develop an integrative framework of AI-powered data capabilities with two core dimensions (AI intelligence and AI action). Research findings clarify how these capabilities enable market sensing, customer profiling, customer linking, and partner bonding. Based on this framework, AI-powered data capabilities are adaptive, relational, and ecosystem-enabling dynamic capabilities, rather than static strategic resources. The study also reveals four boundary conditions that moderate the impacts of AI-powered data capabilities: regulatory constraints, the ripple effects of privacy initiatives, social privacy sentiments, and AI interoperability. These findings offer both theoretical advancement and practical guidance for AI-powered marketing strategy.