Smart Supply Chains for a Sustainable Future: Qualitative Insights into AI Applications in Renewable Energy

This paper seeks to explore the implementation of artificial intelligence (AI) within renewable energy supply chains for the impact on operational efficiency, resilience, and sustainability. Given the focus on transforming the entire world towards an effective supply chain using sustainable energy sources, there is strong interest in how AI can aid the optimization of supply chain processes. From the study, ultimately from the qualitative research done through in-depth interviews with industry experts, key themes that relate to what AI can provide the production system related to forecasting accuracy, resource allocation, and real time decision making. Findings show that in addition to reducing the operational cost, AI also enables the adaptability of supply chains and increases its responsiveness to fluctuation on energy demand and external disturbance. Additionally, the study insists that AI will assist in the reduction of emissions, minimization of waste, and supporting the circular economy improvement. However, advantages like low cost of implementation, lack of standardization, concerns about the ethical process of data privacy, as well as lack of skilled manpower, still pose challenges to wider adoption. This research highlights the need for organizations to make the first stride to resolve these issues by investing the necessary means of training and mediated standards for the integration of AI. Finally, this paper provides some meaningful lessons on the possible effects of AI to the renewable energy supply chain, and it is likely that the success of implementing AI can result in important benefits on operational performance and directly contribute to a more sustainable renewable energy landscape. Combination of AI technologies allows for increasing organization competitiveness and insignificant participation in global movement away from dirty energy and towards cleaner energy future.