Artificial intelligence (AI) is increasingly recognized as a transformative tool within environmental and urban infrastructures, promising smart, sustainable, and optimized solutions. However, numerous AI applications face obstacles in achieving these ambitious goals due to technological determinism and fragmented, efficiency-focused approaches that often overlook environmental and societal complexities. As AI and smart infrastructure play pivotal roles in advancing sustainable urban development, there is an urgent need for an integrated approach that prioritizes environmental impact, resilience, and inclusivity. This perspective paper, drawing on the authors’ viewpoints and interpretations, explores the “environmental AI” concept as an enabler of sustainable infrastructure transformation, advocating for a shift from narrow, technocentric solutions to a framework grounded in ecological and social responsibility. The methodological approach involves a systematic review of over 150 articles sourced from databases such as Scopus, Google Scholar, and Web of Science, synthesizing insights from academic research, industry reports, and case studies to identify key gaps and trends in AI applications related to urban planning and sustainability. This comprehensive review is complemented by qualitative assessments of real-world examples illustrating successful Green AI implementations. The paper aims to guide policymakers and planners in adopting AI systems that address efficiency, sustainability, and equity issues in cities.