1
Return

New development: Principal-agent issues when governments embrace AI agents

delete2026-03-01
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PRE
AI
F
Feng, Naikang
C
Chandra, Yanto *
DOI:10.1080/09540962.2026.2642814delete
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deleteOriginal request for help
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Abstract

Abstract

En 中文
The growing presence of agentic AI in public governance is transforming the once familiar, human-bound principal-agent relationship into a multi-directional socio-technical challenge. This article provides a structured analysis of these challenges by dissecting how AI-related agency problems manifest across three critical delegation interfaces: trust delegation between human users (principals) and AI agent systems; hierarchical delegation between senior officials (principals) and lower-level officials (agents) augmented by AI agents; and contractual delegation where government officials (principals) outsource AI development to private firms (agents). At each interface, the authors clarify how delegation drift may arise due to the intensified information asymmetry and goal misalignment, while creating new accountability gaps. Building on this analysis, the article concludes with a discussion on governing AI agents and proposes a forward-looking research agenda for public administration scholars. As public agencies adopt autonomous 'agentic AI', traditional principal-agent relationships in public administration are fundamentally transforming. This article offers a roadmap for senior administrators, digital transformation chiefs, and procurement officers modernizing government services. The authors demystify algorithmic governance risks by mapping how AI complicates three critical principal-agent delegation interfaces: direct delegation to AI systems, hierarchical delegation to AI-augmented staff, and contractual delegation to private tech vendors. By identifying where goal misalignment, information asymmetries, and 'delegation drift' emerge, this article provides practitioners with a practical diagnostic framework. Ultimately, this equips public sector leaders to anticipate agency problems before they manifest, design robust oversight mechanisms, align vendor incentives, and confidently harness AI innovation while maintaining effective control over public service delivery. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)'(sic)(sic)(sic)AI', (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)-(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic):(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)'(sic)(sic)(sic)(sic)'(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)AI(sic)(sic).
Keywords:
Artificial bureaucrats
digital government
generative AI (GenAI)
principal-agent problem
public governance
public services

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