Harnessing artificial intelligence for sustainable urban development: advancing the three Zeros method through innovation and infrastructure
Abstract Integrating artificial intelligence (AI) into sustainable urban development presents an innovative pathway for addressing global environmental and socio-economic challenges. This study examines how AI technologies—such as machine learning, the Internet of Things (IoT), and big data analytic...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-07436-1 |
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| Summary: | Abstract Integrating artificial intelligence (AI) into sustainable urban development presents an innovative pathway for addressing global environmental and socio-economic challenges. This study examines how AI technologies—such as machine learning, the Internet of Things (IoT), and big data analytics—can advance the three zeros method, a sustainability framework proposed by Nobel laureate Muhammad Yunus, which focuses on zero carbon emissions, zero poverty, and zero waste. By analyzing panel data across 50 countries and incorporating case studies, the research highlights AI’s role in promoting carbon neutrality, economic inclusivity, and waste reduction. The findings reveal that AI-driven R&D innovation exerts the most decisive influence on sustainability, followed by AI-powered infrastructure, while market advantage plays a comparatively more minor role. Additionally, the study uncovers regional disparities in AI’s impact, with the most significant benefits observed in countries at upper-middle levels of sustainable development. Moreover, urbanization serves as a threshold factor, altering AI’s effects on sustainability. When urbanization is below a critical level, AI-driven innovation and infrastructure support sustainability, whereas the AI market advantage inhibits it. However, infrastructure may hinder sustainable development beyond this threshold while AI market mechanisms become more influential. These insights underscore the need for policymakers to tailor AI-driven sustainability strategies based on urbanization dynamics and regional development levels. |
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| ISSN: | 2045-2322 |