Abstract

The increasing adoption of Artificial Intelligence (AI) has transformed how Agile software development teams manage performance and productivity. This study investigates the impact of AI tool usage on developer productivity and team efficiency within Agile environments. Using the AI-Driven Agile IT Developers Dataset, the research applies a combination of descriptive analysis, correlation analysis, multiple regression models, and Random Forest techniques to examine the relationships between AI tool utilization and performance outcomes. The results indicate that AI Tool Usage Level is a strong and consistent predictor of both individual productivity and team efficiency, outperforming traditional factors such as experience level and workload. Collaboration also contributes positively to performance, while excessive workload is associated with reduced outcomes, suggesting that managerial practices remain critical even in AI-augmented settings. The consistency of findings across linear and non-linear models highlights the robustness of AI tools as performance enablers in Agile teams. These findings contribute to the literature on Agile management and AI-enabled work systems by providing empirical evidence on the role of AI tools in shaping performance dynamics. From a managerial perspective, the study emphasizes the importance of integrating AI technologies with collaborative practices and effective workload management to maximize their performance benefits.

Keywords: Agile Performance Management, Artificial Intelligence Tools, Developer Productivity, Team Efficiency, Software Development Management

How to Cite:

Suhartono, S. & Nabila, Z., (2026) “Agile Developer Performance Management in the AI Era: Analysing the Impact of AI Tools on Productivity and Team Efficiency”, Agile Management 1(1), 31-45. doi: https://doi.org/10.63913/am.v1i1.125