The State of Generative AI in Software Development: Insights from Literature and a Developer Survey
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866915870841765888 |
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| author | Gurgul, Vincent Gubela, Robin Lessmann, Stefan |
| author_facet | Gurgul, Vincent Gubela, Robin Lessmann, Stefan |
| contents | Generative Artificial Intelligence (GenAI) rapidly transforms software engineering, yet existing research remains fragmented across individual tasks in the Software Development Lifecycle. This study integrates a systematic literature review with a survey of 65 software developers. The results show that GenAI exerts its highest impact in design, implementation, testing, and documentation, where over 70 % of developers report at least halving the time for boilerplate and documentation tasks. 79 % of survey respondents use GenAI daily, preferring browser-based Large Language Models over alternatives integrated directly in their development environment. Governance is maturing, with two-thirds of organizations maintaining formal or informal guidelines. In contrast, early SDLC phases such as planning and requirements analysis show markedly lower reported benefits. In a nutshell, GenAI shifts value creation from routine coding toward specification quality, architectural reasoning, and oversight, while risks such as uncritical adoption, skill erosion, and technical debt require robust governance and human-in-the-loop mechanisms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_16975 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The State of Generative AI in Software Development: Insights from Literature and a Developer Survey Gurgul, Vincent Gubela, Robin Lessmann, Stefan Software Engineering Artificial Intelligence Computers and Society Emerging Technologies Human-Computer Interaction Generative Artificial Intelligence (GenAI) rapidly transforms software engineering, yet existing research remains fragmented across individual tasks in the Software Development Lifecycle. This study integrates a systematic literature review with a survey of 65 software developers. The results show that GenAI exerts its highest impact in design, implementation, testing, and documentation, where over 70 % of developers report at least halving the time for boilerplate and documentation tasks. 79 % of survey respondents use GenAI daily, preferring browser-based Large Language Models over alternatives integrated directly in their development environment. Governance is maturing, with two-thirds of organizations maintaining formal or informal guidelines. In contrast, early SDLC phases such as planning and requirements analysis show markedly lower reported benefits. In a nutshell, GenAI shifts value creation from routine coding toward specification quality, architectural reasoning, and oversight, while risks such as uncritical adoption, skill erosion, and technical debt require robust governance and human-in-the-loop mechanisms. |
| title | The State of Generative AI in Software Development: Insights from Literature and a Developer Survey |
| topic | Software Engineering Artificial Intelligence Computers and Society Emerging Technologies Human-Computer Interaction |
| url | https://arxiv.org/abs/2603.16975 |