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AI-Driven Regenerative Intelligence for Ecological Restoration and Climate Action

K. AravinthanAnorgul AshirovaS. AarthiMarwadi University, Rajkot, IndiaR. N. RavikumarMarwadi University, Rajkot, IndiaBabamuratov BekzodTermez University of Economics and Service, Termez, UzbekistanUlugbek VosiqovKimyo International University in Tashkent, Tashkent, Uzbekistan
ABI

Abstract

The chapter explores the way the Artificial Intelligence can go beyond carbon mitigation to ecological regeneration and restoration-oriented governance of climate action. It states that AI can be the most useful in combination with the ecological objectives, adaptive planning, governance safeguards, and long-term resilience. To reinforce this stand, the chapter presents the AERSI framework, which relates environmental sensing, analytical intelligence, adaptive decision support, integration to governance, and sustainability responsibility. The targeted literature review and analytical evidence reveal that the use of AI can reinforce the monitoring, predictive planning, and restoration decisions; yet, it is conditional to the quality of data, institutional capacities, local involvement, and ecological legitimacy. The chapter concludes that AI can only be used as restoration infrastructure through a combination of technological ability, governance responsibility, and regenerative outcomes.

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