Environmental sustainability in supply chains is no longer considered a compliance concern. It has become a strategic capability challenge, as firms seek to use Generative artificial intelligence (Gen‐AI) to improve decision quality, resource efficiency and responsible operations. However, despite growing interest in Gen‐AI, its adoption for green and responsible supply chains remains limited in developing countries where policy support, digital readiness and organizational preparedness are major issues. Therefore, based on dynamic capabilities theory, the present study examines how firms can build the capabilities required to adopt Gen‐AI for environmentally sustainable and responsible supply chain practices. First, this study identifies key adoption enablers through a structured literature review. Then, these enablers are validated using a survey based on a 5‐point Likert scale. In the main analytical model, a Grey network map (GNM) based on Grey‐Decision‐making trial and evaluation laboratory (Grey‐DEMATEL) approach is used to examine the causal relationship among the validated enablers and to identify driving and dependent factors under the conditions of uncertainty. The findings of this study reveal that government and policy support, as well as top management support, are the main causal enablers and indicate that strategic leadership can help in the adoption of Gen‐AI for green and responsible supply chains. Also, knowledge management, collaborative culture, and a global collaboration network are the main outcome enablers, which are influenced by causal enablers. The findings suggest a few policy actions, such as the design of sector‐focused AI adoption guidelines, targeted incentives for green digital infrastructure and national capability‐building programmes to support managerial and workforce readiness. The study contributes by offering a validated and structured framework that explains how Gen‐AI adoption can be strategically enabled to support green and responsible supply chains.