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Unlocking the Potential: Exploring the Impact of Generative Artificial Intelligence in Agile Software Engineering
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2025-05
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Business Administration/Interdisciplinary
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https://doi.org/10.34944/tc11-w831
Abstract
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.
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