Artificial Intelligence and Epistemic Authority: A Conceptual Framework for Knowledge Legitimacy, Organisational Performance and Economic Growth
Résumé
Artificial Intelligence (AI) is increasingly reshaping how knowledge is produced, validated, and applied within organisations, institutions, and economies. While existing studies often examine AI as a tool for automation, productivity enhancement, and decision support, less attention has been given to how AI-generated outputs acquire epistemic legitimacy and exercise authority-like influence over organisational and economic decision-making. This conceptual study develops a framework explaining how AI adoption contributes to economic growth through organisational performance, productivity, innovation, competitiveness, legitimacy, and institutional support. Drawing on authority theory and institutional theory, with supporting insights from creative destruction, agency, and ethical perspectives, the paper argues that AI-driven growth depends not only on technological capability but also on trust, explainability, governance, human capital, technical infrastructure, and regulatory clarity. The simplified framework positions AI adoption as the independent variable and economic growth as the outcome. Epistemic legitimacy and organisational performance operate as sequential mediating mechanisms, while AI readiness, comprising AI knowledge, AI capability, human capital, and technical infrastructure, serves as an enabling condition. The institutional environment, reflected in institutional quality and legal and regulatory clarity, moderates the extent to which AI-generated outputs acquire legitimacy and contribute to organisational and economic.The study contributes to the literature by distinguishing AI’s role as a productivity-enhancing technology from its authority-like epistemic and economic functions. These functions do not arise from consciousness, moral agency, or autonomous judgment, but from the extent to which organisations and institutions treat AI-generated outputs as credible, actionable, and legitimate.The framework is particularly relevant for emerging economies, where weak infrastructure, limited finance, skills shortages, regulatory uncertainty, and fragile institutional trust may constrain AI-driven development. The paper concludes that AI’s contribution to economic growth is conditional rather than automatic and requires coordinated investment in human capacity, institutional governance, responsible regulation, and technological readiness.
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