A Qualitative Exploration on Artificial Intelligence and Renewable Energy Integration in Supply Chains

This study explores the integration of artificial intelligence (AI) within renewable energy supply chains, examining its impact on operational efficiency, resilience, and sustainability. As the world transitions toward sustainable energy sources, the role of AI in optimizing supply chain processes has gained significant attention. Through qualitative research involving in-depth interviews with industry experts, the study identifies key themes related to AI's contributions, including enhanced forecasting accuracy, improved resource allocation, and real-time decision-making capabilities. The findings highlight that AI not only reduces operational costs but also increases the adaptability of supply chains to fluctuations in energy demand and external disruptions. Furthermore, the study emphasizes AI’s role in promoting sustainability by facilitating emissions reductions, waste minimization, and supporting circular economy initiatives. Despite these advantages, challenges such as high implementation costs, lack of standardization, ethical concerns regarding data privacy, and a shortage of skilled personnel persist, potentially hindering widespread adoption. The research underscores the necessity for organizations to proactively address these challenges through strategic investments in training and the establishment of clear standards for AI integration. Ultimately, this study provides valuable insights into the transformative potential of AI in renewable energy supply chains, suggesting that its successful implementation can lead to significant improvements in operational performance and contribute to a more sustainable energy landscape. By leveraging AI technologies, organizations can enhance their competitiveness while actively participating in the global effort toward a cleaner and more efficient energy future.