Integrating generative AI into agile methodologies : exploring benefits, challenges, and emerging practices

Abstract

Software has changed many sectors, from manufacturing and finance to entertainment and space exploration. At the same time, Agile methodologies have revolutionized software development by prioritizing rapid iterations, teamwork, and adaptability. Now, with the rise of Generative AI (GenAI), we’re seeing another major shift. GenAI is not just automating routine tasks but it’s providing predictive insights and enhancing decision-making in ways that directly impact development cycles. But how does GenAI fit into Agile frameworks?. This study finds the answers to the question based on ten semi-structured interviews with professionals from startups and mid-sized enterprises. All the participants have hands-on experience in Agile methodologies and GenAI.

This research identifies best practices for adopting GenAI tools from GitHub Copilot to advanced analytics dashboards within Agile frameworks. The findings reveal that while GenAI-driven automation can shorten feedback loops and enhance strategic focus, its successful integration requires the right culture, strong data governance, and a careful balance to avoid undermining Agile’s core human-centric values. The thesis concludes with practical guidelines and recommendations for sustainable GenAI-Agile integration which preserves Agile’s people centric approach while utilizing GenAI’s transformative potential.