This analysis highlights key benefits and risks of AI in software engineering, suggesting effective implementation strategies.
The paper presents practical applications of AI assistants in everyday software engineering: requirement formalization, code scaffolding, SQL/migrations support, log‑based fault localization, test generation, documentation upkeep, and CI/CD optimization. We summarize observable benefits (time savings, defect reduction), typical risks (hallucinations, data leakage, licensing), and a lightweight evaluation method based on before/after measurements on real backlog items. Implementation guidelines for phased adoption are provided.
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Омаралиев et al. (2025) studied this question.
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