Enhancing Software Engineering With AI: Innovations, Challenges, and Future Directions

Software engineering, along with the incorporation of Artificial Intelligence (AI), has emerged as a new technological vantage point that has permanently changed classical development practices and processes for any phase and aspect of the software lifecycle. In particular, this systematic literature review, which includes 135 peer‐reviewed papers extracted from the years 2010 to 2025, follows PRISMA guidelines. It examines modern instances of AI‐based requirements analysis, automated code transformation, predictive system modeling, proactive fault monitoring and detection, and advanced project guidance systems. Technologies can be powerful tools for increasing productivity and effectiveness and strengthening the quality of software development while making technology more complex—technologically, organizationally, and ethically. The generalization, explainability, privacy and algorithmic bias challenges of the model are discussed in detail. This paper shows how AI is helping companies to predict defects, automatically identify errors and optimize the software development. It also highlights the significant adoption barriers to these technologies for organizations. The review combines new industry research with existing practice to offer practical guidance on how these implementation challenges can be overcome and the ethical use of AI can be promoted. In contrast to existing reviews concentrating on isolated stages, the study offers an integrated review through life phases, distinctive ethical frameworks and a roadmap for adoption. Takeaway: Sustainable AI deployment in SE needs interdisciplinary collaboration, ethical oversight, and a mixture of guidelines to balance technology efficiency with responsibility. The paper highlights that interdisciplinary cooperation and ethical framings are requirements to integrate AI into software engineering in a sustainable, straightforward way. This review can be utilized as a guide for authors, scientists/practitioners, and policymakers in articulating the intellectual‐practical gap.

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Publication Details

Journal
IET Software
Published
2025-01-01
DOI
https://doi.org/10.1049/sfw2/5691460
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Software Engineering With AI: Innovations, Challenges, and Future Directions

Omar Alghushairy, Ali Daud, Sunawar Khan, Tahir Abbas et al.
IET Software
Software Engineering Techniques and Practices
article

Enhancing Software Engineering With AI: Innovations, Challenges, and Future Directions

Omar Alghushairy, Ali Daud, Sunawar Khan, Tahir Abbas, Shujaat Ali Rathore, Amira Turki
article en

Abstract

Software engineering, along with the incorporation of Artificial Intelligence (AI), has emerged as a new technological vantage point that has permanently changed classical development practices and processes for any phase and aspect of the software lifecycle. In particular, this systematic literature review, which includes 135 peer‐reviewed papers extracted from the years 2010 to 2025, follows PRISMA guidelines. It examines modern instances of AI‐based requirements analysis, automated code transformation, predictive system modeling, proactive fault monitoring and detection, and advanced project guidance systems. Technologies can be powerful tools for increasing productivity and effectiveness and strengthening the quality of software development while making technology more complex—technologically, organizationally, and ethically. The generalization, explainability, privacy and algorithmic bias challenges of the model are discussed in detail. This paper shows how AI is helping companies to predict defects, automatically identify errors and optimize the software development. It also highlights the significant adoption barriers to these technologies for organizations. The review combines new industry research with existing practice to offer practical guidance on how these implementation challenges can be overcome and the ethical use of AI can be promoted. In contrast to existing reviews concentrating on isolated stages, the study offers an integrated review through life phases, distinctive ethical frameworks and a roadmap for adoption. Takeaway: Sustainable AI deployment in SE needs interdisciplinary collaboration, ethical oversight, and a mixture of guidelines to balance technology efficiency with responsibility. The paper highlights that interdisciplinary cooperation and ethical framings are requirements to integrate AI into software engineering in a sustainable, straightforward way. This review can be utilized as a guide for authors, scientists/practitioners, and policymakers in articulating the intellectual‐practical gap.

IET SoftwareVol. 2025(1)
Abu Dhabi University (AE), International Islamic University, Islamabad (PK), Bahauddin Zakariya University (PK), University of Azad Jammu and Kashmir (PK), University of Jeddah (SA), University of Business and Technology (SA)
Openalex Percentile: Top 55%
Software Engineering Techniques and Practices
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