Artificial Intelligence and Biodiversity Regeneration

Artificial intelligence (AI) is increasingly recognized as a strategic tool for addressing the urgent challenges of biodiversity conservation and regeneration in rapidly urbanizing cities of the Global South. This chapter critically examines the paradox between the maturity of digital infrastructures and the limited ecological uptake of AI-enabled tools for urban biodiversity management. A systematic review of institutional reports, scientific literature, and pilot initiatives in Morocco, Colombia, and Egypt demonstrates that hybrid approaches (combining low-cost Internet of Things (IoT) sensors, context-adapted AI models, participatory platforms, and innovative financing) can significantly enhance ecological monitoring, risk prediction, and inclusive governance. The analysis reveals that, despite promising results such as high species detection accuracy and large-scale citizen engagement, structural obstacles remain. These include geographic and methodological biases in literature, inequitable access to technology, insufficient methodological standardization, and the need for ethical data governance. Recent studies further emphasize the importance of integrating local knowledge, strengthening South–South cooperation, and adopting open data standards to maximize the legitimacy and effectiveness of AI-driven interventions. The deployment of AI for urban biodiversity in the Global South must go beyond technological innovation to embrace systemic, participatory, and context-sensitive strategies. Only such integrated approaches can unlock the full potential of AI to support resilient, inclusive, and sustainable urban ecosystems in line with the objectives of the 2030 Global Biodiversity Framework.