Trends, Effects, and Future Outlook for the Integration of Artificial Intelligence Technologies in the Energy Sector: The Role of Open Innovation

This paper explores the integration of Artificial Intelligence (AI) in the energy sector, focusing on its impact on operational efficiency, cost reduction, and environmental sustainability. It examines how open innovation fosters collaboration among energy companies, startups, and research institutions to accelerate AI adoption. Despite challenges such as data privacy, regulatory barriers, and infrastructure needs, AI technologies are poised to enhance energy optimization and support global goals like net-zero emissions and increased renewable energy penetration. The paper also looks ahead to the future of AI in energy, highlighting the potential of quantum computing, reinforcement learning, and advanced neural networks in driving further innovation.

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Publication Details

Journal
Mikailalsys Journal of Advanced Engineering International
Published
2025-04-12
DOI
https://doi.org/10.58578/mjaei.v2i2.5391
Citations
1
Primary Topic
Economic and Technological Developments in Russia
Type
article
Field-Weighted Citation Impact
3.45
Controls
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article

Trends, Effects, and Future Outlook for the Integration of Artificial Intelligence Technologies in the Energy Sector: The Role of Open Innovation

Elijah Omoniyi Fatokun
1 citations
Mikailalsys Journal of Advanced Engineering International
Economic and Technological Developments in Russia
3.45
article

Trends, Effects, and Future Outlook for the Integration of Artificial Intelligence Technologies in the Energy Sector: The Role of Open Innovation

Elijah Omoniyi Fatokun
article en
1 citations

Abstract

This paper explores the integration of Artificial Intelligence (AI) in the energy sector, focusing on its impact on operational efficiency, cost reduction, and environmental sustainability. It examines how open innovation fosters collaboration among energy companies, startups, and research institutions to accelerate AI adoption. Despite challenges such as data privacy, regulatory barriers, and infrastructure needs, AI technologies are poised to enhance energy optimization and support global goals like net-zero emissions and increased renewable energy penetration. The paper also looks ahead to the future of AI in energy, highlighting the potential of quantum computing, reinforcement learning, and advanced neural networks in driving further innovation.

Mikailalsys Journal of Advanced Engineering InternationalVol. 2(2)
Ajayi Crowther University (NG)
Openalex Percentile: Top 11%
Economic and Technological Developments in Russia
3.45
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