Artificial Intelligence and Climate Governance: The Emerging Politics of Data-Driven Environmental Policy

Abstract

Artificial intelligence (AI) had emerged as a transformative force in climate governance, reshaping the design and implementation of environmental policies through data-driven decision-making and predictive analytics. This study examined the role of AI in climate governance and explored the political, ethical, and institutional implications of data-driven environmental policy frameworks. Using a qualitative research design based on thematic analysis of secondary data, the study analyzed how AI technologies influenced policy effectiveness, governance structures, and power dynamics. The findings indicated that AI had enhanced climate governance by improving real-time monitoring, predictive capabilities, and policy responsiveness. However, the integration of AI also introduced significant challenges, including algorithmic bias, lack of transparency, data inequality, and accountability issues. The study further revealed that AI-driven governance had reshaped power relations by concentrating data and technological control among a limited number of actors, raising concerns about equity and inclusivity, particularly in developing regions. The study concluded that while AI offered substantial potential for improving climate governance, its effectiveness depended on the development of inclusive, transparent, and ethically grounded policy frameworks. It emphasized the need for regulatory mechanisms, stakeholder engagement, and capacity building to ensure responsible AI adoption. The research contributed to the growing discourse on AI and environmental governance by highlighting the importance of balancing technological innovation with social justice and sustainability objectives