Artificial Intelligence for Smart City Reinvention: A Systematic Literature Review and Conceptual Framework
This study investigates how Artificial Intelligence (AI) can be systematically leveraged to reinvent smart cities by optimizing legacy infrastructures for greater efficiency, sustainability, and inclusivity. In response to the accelerating challenges of global urbanization, the research examines how AI’s predictive, adaptive, and autonomous capabilities can transform existing systems in transportation, energy management, waste management, public safety, and citizen engagement without the financial and environmental costs of large-scale redevelopment. Employing a qualitative and conceptual research design grounded in a systematic literature review, the study analyzed eighty-five scholarly, institutional, and industry sources published between 2020 and 2025. The findings reveal that AI integration significantly enhances operational performance across all urban domains, reducing traffic congestion by up to 25%, improving energy efficiency by 15–20%, and cutting waste management costs by 10–15%. However, the results also indicate that the benefits of AI deployment are unevenly distributed, heavily influenced by governance capacity, ethical oversight, and citizen participation. The study developed a socio-technical framework that positions AI as a central enabler linking technological innovation with governance, ethics, and social inclusion. This framework emphasizes three interdependent pillars: technological intelligence, institutional capacity, and social inclusion as prerequisites for sustainable urban transformation. The research concludes that the reinvention of smart cities requires not merely the adoption of advanced technology but the creation of accountable, human-centered governance systems that ensure equity, transparency, and trust. Ultimately, the study contributes a conceptual and policy-relevant foundation for reimagining AI-enabled cities as adaptive, resilient, and ethically governed ecosystems. It offers practical insights for policymakers, urban planners, and researchers seeking to balance innovation with sustainability, efficiency with equity, and digital progress with human welfare.
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Artificial Intelligence for Smart City Reinvention: A Systematic Literature Review and Conceptual Framework
Semantic Scholar · 2026
Abstract
This study investigates how Artificial Intelligence (AI) can be systematically leveraged to reinvent smart cities by optimizing legacy infrastructures for greater efficiency, sustainability, and inclusivity. In response to the accelerating challenges of global urbanization, the research examines how AI’s predictive, adaptive, and autonomous capabilities can transform existing systems in transportation, energy management, waste management, public safety, and citizen engagement without the financial and environmental costs of large-scale redevelopment. Employing a qualitative and conceptual research design grounded in a systematic literature review, the study analyzed eighty-five scholarly, institutional, and industry sources published between 2020 and 2025. The findings reveal that AI integration significantly enhances operational performance across all urban domains, reducing traffic congestion by up to 25%, improving energy efficiency by 15–20%, and cutting waste management costs by 10–15%. However, the results also indicate that the benefits of AI deployment are unevenly distributed, heavily influenced by governance capacity, ethical oversight, and citizen participation. The study developed a socio-technical framework that positions AI as a central enabler linking technological innovation with governance, ethics, and social inclusion. This framework emphasizes three interdependent pillars: technological intelligence, institutional capacity, and social inclusion as prerequisites for sustainable urban transformation. The research concludes that the reinvention of smart cities requires not merely the adoption of advanced technology but the creation of accountable, human-centered governance systems that ensure equity, transparency, and trust. Ultimately, the study contributes a conceptual and policy-relevant foundation for reimagining AI-enabled cities as adaptive, resilient, and ethically governed ecosystems. It offers practical insights for policymakers, urban planners, and researchers seeking to balance innovation with sustainability, efficiency with equity, and digital progress with human welfare.
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