The Future of Scrum in AI-Driven Software Development: A Systematic Review

Authors

  • Gazi Sabbir Ahammad Bachelor of Software Engineering, School of Computer Science and Artificial Intelligence, Zhengzhou University, Henan, China Author
  • Sujan Acharya Bachelor of Software Engineering, School of Computer Science and Artificial Intelligence, Zhengzhou University, Henan, China Author
  • Ahnaf Aiman Abdi MSc. in Information and Communication Engineering, School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, China Author
  • Golam Mahadi M.Sc in Computer Science, School of Computer science and Technology, Dalian University of Technology, Dalian, Liaoning, China Author

DOI:

https://doi.org/10.47363/JEAST/2026(8)361

Keywords:

Scrum, Agile Methodology, Artificial Intelligence, Software Development, Systematic Review, Distributed Teams, Human Oversight, Project Management

Abstract

Scrum has become one of the most widely used Agile frameworks in software development because of its iterative structure, transparency, and ability to support continuous delivery in changing environments. At the same time, Artificial Intelligence (AI) is reshaping how software teams plan, coordinate, and execute development work. This systematic review examines the future of Scrum in AI-driven software development by analyzing its core principles,
workflow, strengths, limitations, and emerging opportunities. The review synthesizes literature from academic databases and credible industry sources to identify how Scrum is being adapted in response to AI-enabled automation, predictive analytics, intelligent task allocation, communication support, and adaptive planning. The findings show that Scrum remains highly relevant for managing complex and evolving software projects, but its effectiveness depends on strong collaboration, disciplined execution, and organizational support. The review also highlights several challenges, including scope creep, scalability in distributed teams, resistance to change, and ethical concerns related to AI bias and human oversight. Overall, the study concludes that AI is unlikely to replace Scrum, but it is likely to reshape Scrum practices by improving efficiency, decision-making, and coordination while preserving the need for human accountability. The paper further identifies future directions such as AI-assisted backlog management, scalable Agile frameworks, responsible AI governance, and cross-domain adoption of Scrum beyond software engineering.

Author Biographies

  • Gazi Sabbir Ahammad, Bachelor of Software Engineering, School of Computer Science and Artificial Intelligence, Zhengzhou University, Henan, China

    Bachelor of Software Engineering, School of Computer Science and Artificial Intelligence, Zhengzhou University, Henan, China

  • Sujan Acharya, Bachelor of Software Engineering, School of Computer Science and Artificial Intelligence, Zhengzhou University, Henan, China

    Bachelor of Software Engineering, School of Computer Science and Artificial Intelligence, Zhengzhou University, Henan, China

  • Ahnaf Aiman Abdi, MSc. in Information and Communication Engineering, School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

    MSc. in Information and Communication Engineering, School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

  • Golam Mahadi, M.Sc in Computer Science, School of Computer science and Technology, Dalian University of Technology, Dalian, Liaoning, China

    Golam Mahadi, M.Sc in Computer Science, School of Computer science and Technology, Dalian University of Technology, Dalian, Liaoning, China.

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Published

2026-06-24

Issue

Vol. 8 No. 6 (2026): Volume 8 Issue 6

Section

Articles