Generative Artificial Intelligence (AI) has rapidly emerged as a transformative tool for knowledge-intensive sectors such as research, consulting, and R&D. However, organizations face critical questions about how to foster trust in these AI systems, encourage their effective use, and ultimately create value from their adoption. This paper develops a conceptual framework for generative AI adoption grounded in the Technology-Organization-Environment (TOE) model, highlighting the interplay of technological, organizational, and environmental factors in shaping trust, use, and value creation. We briefly review individual-level technology acceptance theories (e.g., TAM and UTAUT) before focusing on the broader TOE context more suited to organizational adoption. The framework proposes that technological factors, organizational factors, and environmental factors, jointly influence both an organization’s trust in generative AI and the extent of its use. Trust is posited as a key mediating enabler: without sufficient trust, even technically sound AI tools may see limited use in knowledge work. When generative AI is trusted and effectively used, organizations can unlock significant value in the form of improved productivity, innovation, and knowledge creation. This conceptual paper contributes a holistic model that can guide future research and practice on generative AI implementation in knowledge-intensive domains. We outline theoretical contributions, practical implications for managers seeking to responsibly integrate generative AI, and suggest avenues for empirical validation of the framework.