0 VIVA-Tech IJRI V1, E8 Article - 1

Impact of Generative AI on Collaborative Software Development


EOI: 10.11242/viva-tech.01.08.058

Download Full Text here



Citation

Chandani Patel,Durga Adhikari Chhetri,Nirali bhatt, "Impact of Generative AI on Collaborative Software Development", VIVA-IJRI Volume 1, Issue 8, Article 1, pp. 1-6, 2025. Published by Master of Computer Applications Department, VIVA Institute of Technology, Virar, India.

Abstract

: The adoption of generative artificial intelligence (AI) in software development has reshaped the way teams collaborate, innovate, and manage complex projects. These AI-driven tools assist in automating code generation, bug detection, and documentation, potentially accelerating development cycles and improving software quality. However, their impact on collaborative software development, where multiple stakeholders interact across different phases of the software lifecycle, remains an area requiring deeper investigation. While AI has demonstrated the ability to enhance efficiency by automating routine tasks, its integration within team-based workflows introduces new challenges related to communication dynamics, decision-making processes, and dependency on AI-generated outputs. This research adopts a mixed-methods approach, incorporating both quantitative and qualitative analyses, to evaluate the influence of generative AI on team collaboration and productivity. A survey was conducted within an organization, gathering responses from 30 professionals in roles such as software developers, quality assurance engineers, project managers, and designers. The findings reveal that AI tools contribute positively by reducing development time, minimizing human errors, and facilitating knowledge sharing. However, concerns regarding AI’s accuracy, over-reliance on automation, and challenges in integrating AI seamlessly with existing development workflows persist. Furthermore, while AI enhances productivity, its role in decision-making remains limited, necessitating human oversight to ensure optimal outcomes. The study underscores the need for structured AI adoption strategies that focus on balancing AI assistance with human expertise. Recommendations include enhanced training programs, the development of more domain-specific AI models, and improved AI-human interaction mechanisms to maximize the benefits while mitigating risks. By providing insights into AI's role in software development teams, this research contributes to the broader discussion on sustainable and efficient AI integration within collaborative software engineering environments.

Keywords

-Artificial Intelligence, Collaboration, Generative AI, Productivity, Software Development

References

  1. L. A. Lee, S. Kim, and H. Park, “The Effects of Generative AI on Coding Skills: A Longitudinal Study,” International Journal of Software Development, 12(1), 2023, pp. 67-82.
  2. T. Imai, “Generative AI in Software Development: A New Era of Productivity,” Journal of Software Innovation, 34(1), 2022, pp. 15-30.
  3. ] L. Chen and Y. Zhao, “The Role of AI in Open-Source Software Development: Opportunities and Challenges,” Open Source Software Journal, 8(3), 2022, pp. 45-60.
  4. J. Smith and K. Jones, “AI as a Mediator in Collaborative Software Development,” Journal of Collaborative Computing, 10(2), 2023, pp. 89-102.
  5. J. Baker and A. Smith, “The Impact of AI-Assisted Coding on Developer Productivity,” Journal of Software Engineering, 45(2), 2023, pp. 123-145.
  6. ] R. Miller and L. Thompson, “Ethical Considerations in the Use of Generative AI in Software Development,” Ethics in Technology Review, 8(3), 2023, pp. 45-59.
  7. J. DeFranco-Tommarello, S. R. Hiltz, C. Perez, F. P. Deek, and J. P. Keenan, “Collaborative Software Development: Experimental Results,” Proceedings of the 36th Hawaii International Conference on System Sciences, 2003.
  8. M. Coutinho, L. Marques, A. Santos, M. Dahia, C. França, and R. de Souza Santos, “The Role of Generative AI in Software Development Productivity: A Pilot Case Study,” AIware 2024: Proceedings of the 1st ACM International Conference on AI-Powered Software, pp. 131-138.
  9. F. Song, A. Agarwal, and W. Wen, “The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot,” arXiv, 2410.02091, 2024. https://doi.org/10.48550/arXiv.2410.02091
  10. Sauvola, J., Tarkoma, S., Klemettinen, M. et al. Future of software development with generative AI. Autom Softw Eng 31, 26 (2024). https://doi.org/10.1007/s10515-024-00426-z.
  11. M.A. Hassan, Impact of Adopting AI Tools by Software Developers Towards Productivity and Sustainability, master’s thesis, Lappeenranta–Lahti University of Technology LUT, Lappeenranta, Finland, 2024.
  12. R. Ulfsnes, N. B. Moe, V. Stray, and M. Skarpen, “Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflow,” arXiv, 2405.01543v1, 2024. https://doi.org/10.48550/arXiv.2405.01543