Closing the Governance Gap in Workplace Generative AI Use: A Proposed AI-Literacy and Adaptive-Governance Framework for Ugandan Organizations

Generative artificial intelligence (GenAI) is becoming embedded in everyday workplace activities, including drafting, summarization, coding, analysis and decision support. Employees may adopt these tools more rapidly than organizations establish policies, approved platforms, technical controls and accountability arrangements. This mismatch can create "Shadow AI": workplace use of AI tools outside formal organizational oversight. Such use may expose personal or confidential information, introduce inaccurate or biased outputs into organizational processes, and make responsibility for AIassisted work difficult to trace. These concerns are especially important for Ugandan organizations, which must manage GenAI within existing data-protection, confidentiality and sectoral obligations while national policy on artificial intelligence continues to develop. Drawing on research on Shadow IT and Shadow AI, AI literacy, information-security compliance and organizational AI governance, this paper proposes an integrated AI-Literacy and Adaptive-Governance Framework. The framework has four mutually reinforcing components: employee AI literacy; risk-based governance of tasks and tools; technical safeguards; and human accountability. It distinguishes low-, medium- and high-risk workplace tasks and proposes proportionate controls rather than relying exclusively on blanket prohibition. Four propositions are developed concerning the relationships between AI literacy and verification behaviour, access to approved tools and unauthorized use, risk-tiered governance and policy compliance, and accountability arrangements and incident reporting. A convergent mixedmethods design is proposed to examine these propositions among employees and managers in selected Ugandan organizations. The paper does not report empirical findings; its contribution is a context-sensitive conceptual framework and a testable research agenda for responsible workplace GenAI adoption.