Democratizing Generative AI for Sustainable Competitive Advantage - Costa, Carlos J. (2026)
As generative artificial intelligence (GenAI) diffuses across industries and becomes broadly accessible, the locus of sustainable competitive advantage shifts from technology ownership toward the quality of employee-level adoption and use. This paper develops a cross-level conceptual framework linking firm-level GenAI investment and governance to individual-level AI democratization, defined as the extent to which employees meaningfully, responsibly, and effectively use GenAI in their daily work. We argue that individual-level AI democratization, grounded in three micro foundations (AI usefulness, ease of use, and AI literacy), mediates the relationship between organizational GenAI investments and sustainable competitive advantage. Drawing on the technology acceptance model, resource-based theory, and emerging empirical evidence on AI productivity effects, we advance six propositions linking perceived usefulness, ease of use, AI literacy, responsible use, and innovation outcomes to organizational transformation and sustained relative performance. The framework provides a measurement scaffold for empirical research and offers managerial guidance on treating GenAI as augmentation infrastructure rather than solely as automation. We conclude by outlining future research directions, including longitudinal and cross-cultural investigations of literacy, governance, and transformation dynamics.