Problem
Research questions and friction points this paper is trying to address.
AI deployment
cybersecurity governance
public sector
governance failure
institutional constraints
AI Deployment and Cyber Governance Failures in Public-Sector Organizations: A Typological Analysis
🤖 AI Summary
This study addresses the governance failures in cybersecurity arising from AI deployment in the public sector, a domain underexplored in existing literature due to insufficient integration of institutional constraints and governance instruments. The authors develop a seven-dimensional typological framework to identify ten root causes of AI-driven governance failure, introducing “velocity asymmetry” as a novel structural mechanism. They critically evaluate five major frameworks—including NIST CSF 2.0 and ISO/IEC 27001—through institutional analysis, typology construction, and coverage matrix assessment, revealing significant gaps in addressing shadow AI, velocity asymmetry, and governance vacuums. Building on these insights, the study proposes an interactive tripartite model linking accountability, operational resilience, and compliance failures, culminating in a design specification for an AI-enabled cybersecurity maturity model tailored to government agencies that explicitly maps current governance frameworks’ coverage gaps in the public sector.
📝 Abstract
The intersection of artificial intelligence adoption, cybersecurity governance, and public sector institutional constraints has not been examined as a unified analytical problem in the existing literature. Studies address AI cybersecurity risks generically, public sector governance independently, and framework adequacy separately. Existing studies have not integrated these three streams to explain specifically how AI adoption causes cybersecurity governance failure in government organizations, nor test existing governance instruments against AI-specific public sector failure causes. This paper ad-dresses that gap. It proposes a seven-domain typology identifying ten specific AI-driven cyber governance failure causes grounded in public sector institutional analysis. It presents a three-pathway failure model showing how accountability failure, opera-tional resilience failure, and compliance failure interact and reinforce each other. It de-livers a structured coverage matrix testing five major governance frameworks (NIST CSF 2.0, ISO/IEC 27001, COBIT, NIST AI RMF, and ISO/IEC 42001) against the typology, finding that no instrument addresses Shadow AI, speed asymmetry, or gov-ernance vacuum at the operational specificity required for public sector application. The paper introduces speed asymmetry as a named structural construct with a specified mechanism. The framework provides the design specification for an AI-enabled cyber-security maturity model for government organizations.
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI governance
cybersecurity failure
public sector
speed asymmetry
shadow AI
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