Data, drones, and due process: Reforming regulatory agency models for environmental enforcement in the age of artificial intelligence

The independent regulatory agency (IRA) model, a cornerstone of modern public administration since the Progressive Era, faces structural disruption as artificial intelligence (AI) and drone technology converge in environmental enforcement. This paper argues that AI and drone deployment do not merely augment agency operational capacity but fundamentally reconfigure the foundations of expertise, transparency, procedural due process, discretion, and accountability on which IRA legitimacy rests and extends this analysis to functionally analogous environmental enforcement bodies that vary considerably in their degree of formal independence and enforcement competence. Through a comparative analysis of the US Environmental Protection Agency, the European Union's (EU) environmental regulatory institutions, and China's MEE—three bodies that occupy markedly different positions on a spectrum of institutional independence and enforcement authority—the paper demonstrates that divergent institutional responses reflect deeply embedded administrative traditions rather than technical necessity and that this institutional variation is itself the analytical lever through which the paper isolates the sources of legitimacy disruption. It proposes a four-pillar reform framework (encompassing algorithmic transparency and expertise redesign, procedural protections for automated enforcement decisions, institutional redesign for algorithmic accountability, and international regulatory harmonisation) grounded in existing legal instruments including the EU AI Act and Organisation for Economic Co-operation and Development AI governance principles. The paper contributes to the International Review of Administrative Sciences centennial conversation on regulatory state evolution by demonstrating that preserving IRA legitimacy in the AI era requires institutional adaptation as profound as any in the agency model's century-long history.