Unlocking the Potential: Exploring the Impact of Generative Artificial Intelligence in Agile Software Engineering

The rise of Generative Artificial Intelligence (GenAI) is revolutionizing Agile software engineering, unlocking new levels of productivity, efficiency, and innovation. As organizations increasingly integrate GenAI-powered tools, understanding their impact on Agile workflows is critical. Industry reports fuel the intrigue—McKinsey (2023) projects up to a 45% reduction in development costs, while Forbes reports an 88% surge in productivity due to AI-driven automation. But how does this translate into real-world Agile practices? This study tackles that question through a rigorous, data-driven assessment based on insights from 260 Agile professionals across diverse roles and industries. Findings reveal that 57% of respondents observed moderate reductions in task completion time, while 21% experienced significant efficiency improvements, affirming GenAI’s role as a powerful productivity enabler. Multiple linear regression analysis identifies task rework reduction as the most significant predictor of efficiency gains (β = 0.469, p < 0.001), highlighting how GenAI-powered automation, and intelligent debugging minimize redundant work and accelerate Agile processes. Sprint speed improvements (β = 0.39, p < 0.001) further optimizes efficiency. While organizational AI support fosters transformation, its direct effect on efficiency is less pronounced (β = 0.079, p = 0.294), suggesting that success depends on strategic execution, not just endorsement. One of the most compelling insights is the dynamic shift in GenAI-driven collaboration. While GenAI enhances knowledge-sharing, workflow disruptions can arise if not implemented thoughtfully (β = -0.22, p = 0.002). Additionally, 43% of respondents cite concerns about AI bias and transparency, underscoring the need for ethical AI governance. This study serves as a guiding framework for organizations, technology leaders, Agile teams, and policymakers, offering actionable insights on how to maximize the benefits of GenAI while addressing integration challenges and guiding them towards a future where human-AI collaboration unlocks unprecedented innovation and efficiency.

Grantor dc:publisher

Temple University. Libraries

Year dc:date.issued

2025

Author dc:creator

• Anand, Pawan

Advisor dc:contributor.advisor

• Rivera, Michael J.

Committee members dc:contributor.committeemember

• Kumar, Subodha
• Di Benedetto, C. Anthony
• Chitturi, Pallavi

• Artificial intelligence
• Information technology
• Business administration
• Agile software engineering
• GenAI
• Generative artificial intelligence
• Productivity
• Software engineering
• Business administration/interdisciplinary

Statement dc:rights

• IN COPYRIGHT- This Rights Statement can be used for an Item that is in copyright. Using this statement implies that the organization making this Item available has determined that the Item is in copyright and either is the rights-holder, has obtained permission from the rights-holder(s) to make their Work(s) available, or makes the Item available under an exception or limitation to copyright (including Fair Use) that entitles it to make the Item available.

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

eng

Repository record dc:identifier.uri

https://scholarshare.temple.edu/handle/20.500.12613/11149

OAI identifier oai:identifier

oai:scholarshare.temple.edu:20.500.12613/11149