This study explores the literature on Green and Sustainable AI through a dual-analytical approach, combining thematic analysis with BERTopic modeling. The research identifies three major thematic clusters: (1) Responsible AI for Sustainable Development, focusing on integrating sustainability and ethics within AI technologies; (2) Advancements in Green AI for Energy Optimization, centering on energy efficiency; and (3) Big Data-Driven Computational Advances, emphasizing AI's influence on socio-economic and environmental aspects. BERTopic modeling uncovers five emerging topics: Ethical Eco-Intelligence, Sustainable Neural Computing, Ethical Healthcare Intelligence, AI Learning Quest, and Cognitive AI Innovation. The study advocates for a unified approach to innovation in AI, promoting environmental sustainability and ethical integrity to foster responsible AI development, aligning with the Sustainable Development Goals. The research highlights the need for integrating ethical and environmental considerations into the AI development lifecycle, offering insights for future research directions and policy interventions.This study explores the literature on Green and Sustainable AI through a dual-analytical approach, combining thematic analysis with BERTopic modeling. The research identifies three major thematic clusters: (1) Responsible AI for Sustainable Development, focusing on integrating sustainability and ethics within AI technologies; (2) Advancements in Green AI for Energy Optimization, centering on energy efficiency; and (3) Big Data-Driven Computational Advances, emphasizing AI's influence on socio-economic and environmental aspects. BERTopic modeling uncovers five emerging topics: Ethical Eco-Intelligence, Sustainable Neural Computing, Ethical Healthcare Intelligence, AI Learning Quest, and Cognitive AI Innovation. The study advocates for a unified approach to innovation in AI, promoting environmental sustainability and ethical integrity to foster responsible AI development, aligning with the Sustainable Development Goals. The research highlights the need for integrating ethical and environmental considerations into the AI development lifecycle, offering insights for future research directions and policy interventions.