Engineers’ Experiences with Artificial Intelligence Integration in Renewable Energy Systems
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Abstract
Artificial Intelligence (AI) is increasingly integrated into renewable energy systems, offering efficiency and reliability in meeting the growing demands of urban environments. Within this technological advancement, the experiences of engineers who design and implement AI-driven systems remain underexplored, particularly regarding the ethical, emotional, and professional dimensions of their engagement. However, prior studies have largely emphasized technical performance, leaving unanswered how engineers themselves make sense of the challenges and opportunities posed by AI integration. This study addresses this gap by adopting an interpretative phenomenological approach to explore the lived experiences of engineers implementing AI in renewable energy projects. Data were collected through semi-structured, in-depth interviews with twelve practicing engineers and analyzed using Interpretative Phenomenological Analysis (IPA) to capture subjective meaning-making processes. The findings reveal four interconnected themes: negotiating technical complexities, managing ethical responsibility, adapting within multidisciplinary teams, and developing trust that fosters professional growth. These findings provide new empirical insights into how engineers construct professional meaning and navigate ethical dilemmas in technologically dynamic contexts. They underscore the dual nature of AI integration—as both a catalyst for innovation and a source of professional tension—highlighting the importance of reflective practice and ethical awareness in engineering design. This study’s primary contribution lies in advancing a human-centered understanding of AI integration, emphasizing that technological adoption in renewable energy systems must account for the experiential and moral dimensions of engineering work. Practically, the research offers implications for organizational leaders and policymakers to design training, support mechanisms, and governance frameworks that foster ethical resilience and interdisciplinary collaboration among engineers. By illuminating these dimensions, the research contributes to a more human-centered framework for AI integration in renewable energy systems and lays the groundwork for future investigations across broader contexts.
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