Responsible AI Strategy, Organizational Knowledge, and Value Creation: Integrating Dynamic Capabilities, the Knowledge-Based View, and Stakeholder Theory

Abstract

This study investigates how responsible AI strategy, conceptualized as a higher-order organizational capability integrating dynamic AI-related capabilities and responsible AI governance, enables firms to create stakeholder-based value through the orchestration of organizational knowledge. The study employs a two-wave, matched-pair, multi-country survey design across AI-adopting firms in Canada and the United States. Data are collected from two key informants per firm (business and AI/IT leaders), yielding approximately 450 usable responses and 210–220 complete matched firm-level pairs used for hypothesis testing. The model is analyzed using partial least squares structural equation modelling (PLS-SEM) in SmartPLS, with bootstrapped mediation and moderation tests and multi-group analysis (PLS-MGA) to examine cross-country differences. The results indicate that organizational knowledge orchestration mediates the relationship between dynamic AI-related capabilities and stakeholder value creation. Responsible AI governance mechanisms strengthen this relationship, underscoring the role of ethical and institutional safeguards in realizing strategic and societal value. Cross-country analysis reveals both shared patterns and contextual differences between Canada and the United States. This study provides a multi-country, firm-level matched-pair empirical integration of dynamic capabilities, the knowledge-based view, and stakeholder theory in the context of responsible AI strategy, offering both theoretical advancement and actionable guidance for managers and policymakers seeking to align AI initiatives with ethical governance and long-term value creation.