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Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector

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  • Chankook Park

    (Division of Climate Change, Hankuk University of Foreign Studies, Yongin 17035, Republic of Korea)

Abstract

The integration of artificial intelligence (AI) in the energy sector offers transformative potential but is hindered by a complex web of interconnected socio-technical challenges. The existing scholarship often addresses these issues in isolation, lacking a practical framework to guide stakeholders through the complexities of responsible deployment. This study addresses this gap by conducting a systematic literature review to develop and propose an integrative, actionable governance framework. The proposed framework is built on four core principles: Trustworthiness, Sustainability, Equity, and Collaborative Adaptation. Crucially, it operationalizes these principles through a four-phased implementation process, a stakeholder-specific action matrix with measurable key performance indicators, and a set of critical success factors. By synthesizing diverse solutions—from technical standards for data and security to governance mechanisms for ethical oversight and workforce transition—into a structured, lifecycle-based approach, this study argues that moving beyond piecemeal fixes is essential for mitigating systemic risks. This framework provides a testable roadmap for future research and a practical guide for policymakers and industry leaders seeking to harness AI’s full potential in a sustainable, ethical, and inclusive manner.

Suggested Citation

  • Chankook Park, 2025. "Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector," Sustainability, MDPI, vol. 17(13), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:5764-:d:1685307
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    References listed on IDEAS

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    1. Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(C).
    2. Emmanuel Ejuh Che & Kang Roland Abeng & Chu Donatus Iweh & George J. Tsekouras & Armand Fopah-Lele, 2025. "The Impact of Integrating Variable Renewable Energy Sources into Grid-Connected Power Systems: Challenges, Mitigation Strategies, and Prospects," Energies, MDPI, vol. 18(3), pages 1-31, February.
    3. Kwon, Soongeol, 2020. "Ensuring renewable energy utilization with quality of service guarantee for energy-efficient data center operations," Applied Energy, Elsevier, vol. 276(C).
    4. Shi, Zhongtuo & Yao, Wei & Li, Zhouping & Zeng, Lingkang & Zhao, Yifan & Zhang, Runfeng & Tang, Yong & Wen, Jinyu, 2020. "Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions," Applied Energy, Elsevier, vol. 278(C).
    5. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    6. Sucheta Nadkarni & V. K. Narayanan, 2007. "Strategic schemas, strategic flexibility, and firm performance: the moderating role of industry clockspeed," Strategic Management Journal, Wiley Blackwell, vol. 28(3), pages 243-270, March.
    7. Pandey, Dharen Kumar & Hunjra, Ahmed Imran & Bhaskar, Ratikant & Al-Faryan, Mamdouh Abdulaziz Saleh, 2023. "Artificial intelligence, machine learning and big data in natural resources management: A comprehensive bibliometric review of literature spanning 1975–2022," Resources Policy, Elsevier, vol. 86(PA).
    8. Zongxu Liu & Hui Guo & Yingshuai Zhang & Zongliang Zuo, 2025. "A Comprehensive Review of Wind Power Prediction Based on Machine Learning: Models, Applications, and Challenges," Energies, MDPI, vol. 18(2), pages 1-17, January.
    9. Zirar, Araz & Ali, Syed Imran & Islam, Nazrul, 2023. "Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda," Technovation, Elsevier, vol. 124(C).
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