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Purpose This study investigates the evolution and future trajectory of artificial intelligence (AI) in advancing environmental sustainability in Egypt and the United Arab Emirates (UAE) from 2015 to 2030. It analyzes how these distinct governance models, centralized policy capacity vs rapid technology-led implementation leverage AI to bridge the “Policy-to-Action” gap regarding resource scarcity and long-term climate resilience. Design/methodology/approach The research employs a longitudinal comparative case study methodology utilizing qualitative document analysis and thematic process tracing to systematically evaluate national AI strategies and legislative frameworks from 2015 through to 2030 strategic targets. It utilizes 2026 benchmarks, including the Government AI Readiness Index 2025 (Oxford Insights, 2026), to assess AI efficacy in water management, energy systems, and urban planning. Findings The analysis reveals a significant policy divergence: the UAE has transitioned to mandatory AI-driven climate reporting via Federal Decree-Law No. 11 (2024a), while Egypt has established global leadership in “Policy Capacity,” achieving a perfect score of 100/100 and ranking 1st in Africa in the 2025 AI Readiness Index. Both nations successfully deploy AI for water management; however, the UAE leads in urban “Net Zero” integration and operational efficiency (e.g. 95% water savings in AI-managed agriculture), while Egypt excels in localized strategic alignment and “Sovereign AI” infrastructure. Findings reveal that while the UAE's Implementation-First model drives faster infrastructure deployment, Egypt's Policy-First approach fosters deeper institutional ownership, though both face a critical energy-water-AI paradox that threatens 2030 sustainability targets. Originality/value This paper provides an original comparative treatment of Arab AI governance by incorporating 2025–2026 strategic updates, including the UAE's January 2026 integration of the National AI System as a Cabinet advisory member. It introduces a novel framework the Policy-to-Action Bridge, highlighting AI as a central pillar of modern environmental legislation and procedural justice rather than merely a technical instrument.
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Bakr et al. (2026) studied this question.
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