Artificial Intelligence and Governance Innovation for Sustainable Cities

As cities face accelerating urbanization and growing sustainability challenges, artificial intelligence (AI) is increasingly becoming a central element of urban governance. Machine-learning models are now optimizing energy systems, computer-vision platforms are monitoring air quality and traffic flows, and generative algorithms are informing equitable housing allocation. However, while these technologies hold significant potential to advance the United Nations (UN) Sustainable Development Goals (SDGs), they also raise pressing concerns regarding algorithmic bias, data privacy, surveillance, and digital exclusion.

This topic invites scholarly contributions that critically examine how AI is reshaping urban governance, planning, and everyday life in pursuit of sustainable development. We welcome rigorous, interdisciplinary research that interrogates both the transformative potential and the trade-offs, risks, and unintended consequences of AI-driven urbanism. Comparative analyses across the Asia-Pacific region and other global contexts are particularly welcome, especially those that engage with national and local strategies on AI-related urban governance and policy innovation.

The Research Topic aims to critically examine AI’s role in developing sustainable cities, addressing both its potential to advance the UN SDGs and its risks, such as algorithmic bias and regulatory gaps, while facilitating interdisciplinary and comparative research. Articles concerning AI’s role in advancing SDGs, including the following themes, are invited:

• Problems of AI’s carbon and environmental footprints and solutions
• AI’s positive and negative impact on labour markets
• Representation of paradigms, knowledge, and languages in training datasets
• Risks of cascading failures in AI-optimized systems during black-swan events
• Innovating regulatory governance that addresses transparency and accountability issues related to AI applications
• AI’s role in the policy processes for sustainable cities
• Fiscal challenges of adopting AI in the public sector
• AI’s role in community building and impact on citizens’ well-being

The Research Topic welcomes papers using qualitative, quantitative, and mixed methods. Both empirical studies and systematic reviews are invited. Local, regional, and global scopes with comparative perspectives are encouraged. Articles can draw theories from multiple disciplines to study research questions of practical significance.

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review

Keywords: Artificial Intelligence, Governance Innovation, Sustainable Cities, Urban Governance, Urban Development, Digital urbanism

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.