The Role of PMOs in the AI Adoption Journey in the Energy Sector: An Exploratory Case Study
Loading...
Authors
Amalraj, Antony
Issue Date
2025-10
Type
Dissertation
Language
en
Keywords
TAI-Cybersecurity PRM , Trustworthy AI , PMO , Business, Engineering, Science, & Technological Innovation
Alternative Title
Abstract
Project management offices (PMOs) are increasingly central to driving strategic alignment and ensuring the successful execution of complex initiatives in the energy sector. As the industry transitions toward renewable energy, infrastructure modernization, and sustainability, PMOs play a vital role in addressing the risks linked to emerging technologies. The U.S. Department of Energy (DOE) identifies artificial intelligence (AI) as a catalyst for grid modernization and decarbonization, aligning with global perspectives that AI will transform project management. The problem this study addressed was the energy sector’s challenges in adopting AI to meet decarbonization targets due to cybersecurity risks. Cybersecurity is critical because of the sector’s role in national security, economic stability, and public safety. The purpose of this qualitative study was to explore how PMOs can help mitigate the cybersecurity risks associated with AI adoption during the transition to renewable energy. A qualitative methodology and exploratory case study design were utilized to examine the PMO’s role in addressing these risks. Building on prior research, this study applied an integrated framework, TAI-Cybersecurity PRM, which embeds context-based cybersecurity risk management into the TAI-PRM process. This framework provides a systematic approach to strengthening security posture when implementing AI technologies. The analysis drew on DOE reports on AI and cybersecurity, along with insights from experienced U.S.-based energy professionals recruited through purposive sampling. The research question guiding the study was: How can PMOs assist in mitigating cybersecurity risks when adopting AI during the transition to renewable energy in the energy sector? The findings were organized into five themes: Trustworthy AI, Context Understanding, Cybersecurity Risks, Risk Management, and the Project Management Office. From these, five categories of practice recommendations emerged: building trustworthy AI, applying a risk-based approach, mitigating cybersecurity threats, increasing awareness of AI-related risks, and strengthening PMO engagement in AI adoption. These recommendations, grounded in existing research and the TAI-Cybersecurity PRM framework, highlight PMOs’ strategic role in balancing innovation with security. Finally, opportunities for future research were identified, including expanding generalizability, addressing ethical and privacy risks, evaluating the impact of evolving AI regulations, and conducting quantitative studies to complement the qualitative findings.