Artificial Intelligence Enabled Eco Marketing Communications and Sustainable Consumer Prioritization

This paper was an attempt to analyse AI-enabled eco-marketing communications with the application of Analytic Hierarchy Process, topic modeling, and sustainability assessment analysis and to project a data-driven evaluation method applicable to identify consumer prioritization of eco-friendly practices. Using a mixed-method approach with advanced computational knowledge in this study, an integrated framework was computed and classified into hierarchical levels of consumer engagement. During the process, a set of sustainability metrics were selected (here, carbon footprint, supply chain transparency, and ethical compliance) together with the degree of consumer alignment in sustainability of marketing strategies. The proposed work also intends to expand and validate in-depth research using the Analytic Hierarchy Process to discover, analyze, and synthesize an accessible overview of the interconnections surrounding the numerous decision-making factors involved with the use of AI in eco-marketing communications. This research will contribute significantly to addressing the ongoing sustainability concerns of the global population in their use of AI-driven technologies in various eco-marketing applications by addressing technical implementation limitations, cultural differences, and other contextual barriers. It will also help to bridge the gap between corporate eco-initiatives and the environmentally conscious population by addressing consumer preference inconsistencies. By giving attention to this emerging field, this piece of research will provide a better foundation for how to optimize eco-marketing communications and overcome the knowledge and implementation gap of sustainable practices among diverse consumer demographics from several perspectives.