The Role of Artificial Intelligence and Machine Learning in Advancing Sustainability Initiatives and Monitoring Global Progress

Abstract

The pace of climate change, urbanization, and resource decadence has further exacerbated the necessity to sustainably monitor and govern, in alignment with the United Nations Sustainable Development Goals. The proposed study would analyze the role of Artificial Intelligence and Machine Learning in supporting sustainability efforts and enhancing the accuracy, transparency, and policy relevance of sustainability monitoring frameworks in the context of major areas. The research is informed by the secondary, policy-relevant sustainability indicators acquired through international sources, such as United Nations databases, World Bank repositories, and global smart city platforms. Indicators of energy efficiency, carbon emission, urban mobility, and waste management were conceptually examined to reflect sustainability performance across the pre- and post-AI-driven intervention. Conceptual mixed methods were used by incorporating quantitative and qualitative performance measurements and policymaking.  RMSE, MAE, and R2 were used to determine model performance, whereas the sustainability impact was measured using percent improvement and SDG alignment. The outcomes suggest that AI/ML models have high predictive performance, and their explanatory power of carbon emission (R2 = 0.91) and energy consumption (R2 = 0.89) is high. The analysis of the sustainability impact showed that the adoption of AI has brought about significant changes, namely, a 25.8% energy efficiency improvement, a 16.3% decrease in CO2 emissions, a 23.8% decrease in traffic congestion, and a 38.8% increase in the rate of waste recycling. The additional insights of clustering and forecasting revealed the differences in regions and the long-term advantages of the long-lasting integration of AI. The research comes to a conclusion that AI and ML can be powerful facilitators to sustainability monitoring and policy assessment in the case of transparent government and institutional preparedness. AI-based systems offer practical recommendations on the development of SDGs and enhanced evidence-based sustainability governance.