The State of Generative AI in Software Development: Insights from Literature and a Developer Survey
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 21 of its 64 references that are in the map. First posted on arXiv 17 Mar 2026.
Builds on
21 of 64 references.
References · 21
- 2021Evaluating Large Language Models Trained on Codecited by 8,320
- 2021Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributionscited by 431
- 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 274
- 2023Generative AIcited by 120
- 2022Productivity Assessment of Neural Code Completioncited by 98
- 2023Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPTcited by 71
- 2024Using AI-Based Coding Assistants in Practice: State of Affairs, Perceptions, and Ways Forwardcited by 45
- 2023Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attackscited by 33
- 2024Requirements are All You Need: From Requirements to Code with LLMscited by 22
- 2025Language Models for Code Optimization: Survey, Challenges and Future Directionscited by 15
- 2024Empowering Agile-Based Generative Software Development through Human-AI Teamworkcited by 12
- 2023Developer Experiences with a Contextualized AI Coding Assistant: Usability, Expectations, and Outcomescited by 9
9 more
- 2024Exploring Human-AI Collaboration in Agile: Customised LLM Meeting Assistantscited by 9
- 2025The Effects of GitHub Copilot on Computing Students' Programming Effectiveness, Efficiency, and Processes in Brownfield Programming Taskscited by 9
- 2023PromptInfuser: How Tightly Coupling AI and UI Design Impacts Designers' Workflowscited by 8
- 2024Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflowcited by 6
- 2025Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Studycited by 5
- 2024Harnessing the Potential of Gen-AI Coding Assistants in Public Sector Software Developmentcited by 3
- 2025The Impact of Large Language Models (LLMs) on Code Review Processcited by 3
- 2025CelloAI: Leveraging Large Language Models for HPC Software Development in High Energy Physicscited by 2
- 2025A Case Study Investigating the Role of Generative AI in Quality Evaluations of Epics in Agile Software Developmentcited by 1
Built on by
Citing papers per year: 2026: 2.
2 papers.
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- 2026Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agendacited by 0
- 2026Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agenda21 Aug 2026
- 2026Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI1 Jul 2026