Challenges and Opportunities for Generative AI in Software Engineering: A Managerial View

Generative artificial intelligence (GenAI) has shown a strong potential to automate tasks, increase productivity, and enhance software quality. Managers have an important role in adopting GenAI as they lead strategic planning and team coordination. This study examines the software engineering tasks that managers consider suitable for large language models (LLMs), as well as the role of management and education in software engineering practices. The study reviews current applications in practice and explores the challenges encountered during implementation. We conducted a workshop with managers from diverse organizations to collect insights on the growing use of LLMs in areas such as code development, debugging, documentation, and training. The discussion highlighted several key concerns, including intellectual property issues, quality assurance, and integration difficulties. Overall, our findings suggest that LLMs can potentially transform software engineering practices if technical and organizational challenges are carefully addressed.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3728718
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.57
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article

Challenges and Opportunities for Generative AI in Software Engineering: A Managerial View

Lena‐Maria Öberg, Sergio Rico
2 citations
Big Data and Business Intelligence
4.57
article

Challenges and Opportunities for Generative AI in Software Engineering: A Managerial View

Lena‐Maria Öberg, Sergio Rico
article en
2 citations

Abstract

Generative artificial intelligence (GenAI) has shown a strong potential to automate tasks, increase productivity, and enhance software quality. Managers have an important role in adopting GenAI as they lead strategic planning and team coordination. This study examines the software engineering tasks that managers consider suitable for large language models (LLMs), as well as the role of management and education in software engineering practices. The study reviews current applications in practice and explores the challenges encountered during implementation. We conducted a workshop with managers from diverse organizations to collect insights on the growing use of LLMs in areas such as code development, debugging, documentation, and training. The discussion highlighted several key concerns, including intellectual property issues, quality assurance, and integration difficulties. Overall, our findings suggest that LLMs can potentially transform software engineering practices if technical and organizational challenges are carefully addressed.

Mid Sweden University (SE)
Openalex Percentile: Top 5%
Big Data and Business Intelligence
4.57
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