Strategic Alignment Patterns in National AI Policies
Mohammad Hossein Azin, Hessam Zandhessami

TL;DR
This paper presents a visual mapping methodology to evaluate strategic alignment in national AI policies, revealing diverse patterns of coherence and misalignment across countries' governance models.
Contribution
It introduces a novel visual analysis approach combining matrix visualization and network analysis for assessing policy coherence in AI strategies.
Findings
Distinct alignment archetypes identified across governance models
High-coherence strategies link economic objectives with innovation funding
Common vulnerabilities include misalignment between ethical goals and regulation
Abstract
This paper introduces a novel visual mapping methodology for assessing strategic alignment in national artificial intelligence policies. The proliferation of AI strategies across countries has created an urgent need for analytical frameworks that can evaluate policy coherence between strategic objectives, foresight methods, and implementation instruments. Drawing on data from the OECD AI Policy Observatory, we analyze 15-20 national AI strategies using a combination of matrix-based visualization and network analysis to identify patterns of alignment and misalignment. Our findings reveal distinct alignment archetypes across governance models, with notable variations in how countries integrate foresight methodologies with implementation planning. High-coherence strategies demonstrate strong interconnections between economic competitiveness objectives and robust innovation funding…
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Taxonomy
TopicsSustainability and Climate Change Governance · Ethics and Social Impacts of AI · Qualitative Comparative Analysis Research
