Harnessing Artificial Intelligence for Advancements in Electrical Engineering: A Systematic Literature Review of Applications, Challenges, and Future Trends

ABSTRACT Artificial intelligence (AI) is increasingly recognized as a vital tool in electrical engineering, offering automation, error reduction, and enhanced accessibility. However, its adoption has lagged compared to other fields, highlighting a need for a comprehensive examination of its applications and challenges. This study systematically reviews AI applications in electrical engineering, classifying research findings to uncover progress, challenges, and opportunities. It aims to identify trends, gaps, and implications to guide future research and practical applications. A systematic literature review (SLR) was conducted, analyzing studies published between 2014 and 2024. Fifty‐seven publications meeting inclusion criteria were categorized into five themes: AI algorithms, power engineering, smart grid technologies, electric vehicle systems, and AI integration. The review revealed growing interest in AI applications within electrical engineering, with a significant rise in publications, particularly from China. AI algorithms demonstrated broad applicability and versatility across various domains, highlighting their potential for innovation. Additionally, there is a considerable opportunity for developing and applying frameworks to test AI innovations in electrical engineering. AI integration in electrical engineering has advanced significantly in areas such as power engineering, smart grid technologies, and electric vehicle systems. However, substantial untapped potential remains, particularly in developing frameworks for testing AI innovations. This review underscores the importance of global research efforts and identifies promising directions for advancing AI applications in electrical engineering research and practice.

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Publication Details

Journal
Computer Applications in Engineering Education
Published
2025-10-04
DOI
https://doi.org/10.1002/cae.70083
Citations
1
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
1.21
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article

Harnessing Artificial Intelligence for Advancements in Electrical Engineering: A Systematic Literature Review of Applications, Challenges, and Future Trends

Michelle Nguyen, Javeed Kittur
1 citations
Computer Applications in Engineering Education
Machine Fault Diagnosis Techniques
1.21
article

Harnessing Artificial Intelligence for Advancements in Electrical Engineering: A Systematic Literature Review of Applications, Challenges, and Future Trends

Michelle Nguyen, Javeed Kittur
article en
1 citations

Abstract

ABSTRACT Artificial intelligence (AI) is increasingly recognized as a vital tool in electrical engineering, offering automation, error reduction, and enhanced accessibility. However, its adoption has lagged compared to other fields, highlighting a need for a comprehensive examination of its applications and challenges. This study systematically reviews AI applications in electrical engineering, classifying research findings to uncover progress, challenges, and opportunities. It aims to identify trends, gaps, and implications to guide future research and practical applications. A systematic literature review (SLR) was conducted, analyzing studies published between 2014 and 2024. Fifty‐seven publications meeting inclusion criteria were categorized into five themes: AI algorithms, power engineering, smart grid technologies, electric vehicle systems, and AI integration. The review revealed growing interest in AI applications within electrical engineering, with a significant rise in publications, particularly from China. AI algorithms demonstrated broad applicability and versatility across various domains, highlighting their potential for innovation. Additionally, there is a considerable opportunity for developing and applying frameworks to test AI innovations in electrical engineering. AI integration in electrical engineering has advanced significantly in areas such as power engineering, smart grid technologies, and electric vehicle systems. However, substantial untapped potential remains, particularly in developing frameworks for testing AI innovations. This review underscores the importance of global research efforts and identifies promising directions for advancing AI applications in electrical engineering research and practice.

Computer Applications in Engineering EducationVol. 33(6)
University of Oklahoma (US)
Openalex Percentile: Top 16%
Machine Fault Diagnosis Techniques
1.21
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Harnessing Artificial Intelligence for Advancements in Electrical Engineering: A Systematic Literature Review of Applications, Challenges, and Future Trends — Michelle Nguyen, Javeed Kittur · Computer Applications in Engineering Education (2025) | TGRS Research Map | TGRS