In an open space, this study thus concentrates on examining how artificial intelligence combined with Green IT adoption impacts the efficiencies in supply chains that are towards being more sustainable and better still green. The booming approval wave of artificial intelligence as a strong driver of change in diverse industries has even more made it evident how CE practices are now developing, especially in this case, within the field of manufacturing. Presently, a vast convergence of AI, sustainability, and Corporate Social Responsibility marks an important area as it resonates with the idea that efficient and innovative developments are ensured through AI, which in turn influences the site as much as possible to the environment. In addition, this discusses some research gaps related to Green Supply Chain Management by proposing frameworks for environmental, economic, and market performance evaluation of organizations, thus rendering significant clues on resource optimization in a circular economy.On different grounds, this is entitled to the role of industry 4.0 technologies, which like AI and blockchain, would embrace green manufacturing practices and promote recycling. The new possibilities of sustainability through supply chains are brought by these technologies, which also help reduce carbon emissions, operational efficiency, and much more transparent ways of doing things. These studies have also identified some of the barriers in creating an environment for their applications as sustainable innovation, which include organizational challenges and need for training of employees to make use of the full potential of digitalization.
The objectives of the study include analyzing the impact of AI in green IT, identifying performance evaluation frameworks for GSCM, and exploring the barriers to AI adoption in IT supply chains. The main results present the enablers of digital technologies for sustainable supply chains while also showing their importance in overcoming regulatory and workforces’ challenges. Most important implications include a need for transformative approaches in integrating AI into supply chain strategies for long term environmental and economic sustainability