AUTOMATION OF AGILE MANAGEMENT PROCESSES USING N8N: DEVELOPMENT OF AN INTELLIGENT PROJECT MANAGEMENT ECOSYSTEM

Abstract

The article presents a comprehensive approach to automating Agile management processes using the opensource integration platform n8n as the core component of an intelligent project management ecosystem. The study focuses on designing an architecture that integrates Jira, Notion, Slack, Google Workspace, and other digital tools widely used by IT teams. The research highlights that the increasing complexity of Agile environments – driven by the growing number of tasks, communication channels, and software tools – leads to higher administrative workload, reduced transparency of processes, and delays in managerial decision-making. Therefore, automation and intelligent orchestration have become critical capabilities for modern Agile teams. The purpose of the study is to develop a methodological and technological framework for implementing an automated Agile project management ecosystem based on n8n and to evaluate its impact on key team performance indicators. The methodology integrates an analytical review of modern automation tools, the design of an integration architecture, experimental implementation of workflow scenarios, and comparative analysis of two Scrum teams – one functioning traditionally and another supported by automated n8n workflows. Implemented workflows include automatic task creation, cross-system status synchronization, daily reporting, velocity analytics, and AI-driven risk prediction powered by OpenAI modules. The scientific novelty of the study lies in the development of an intelligent, low-code-based automation architecture that integrates Agile practices with data synchronization, analytical components, and generative AI capabilities. Compared to traditional tools, the proposed model enables integrated management of the product lifecycle, reduces manual administrative workload, increases transparency, and supports adaptive decision-making within Agile 2.0 frameworks. Experimental findings demonstrate that using n8n automation reduced administrative workload by 65%, increased task status relevance to 95%, decreased sprint delays by more than half, and significantly improved overall team satisfaction. These results confirm the effectiveness of the proposed ecosystem and its potential to enhance project transparency, workflow efficiency, and Agile team productivity. The study concludes that n8n can successfully serve as the foundation of an intelligent Agile project management ecosystem. The proposed architecture and workflow scenarios can be scaled to various organizational contexts. Future research directions include developing AI-driven orchestration using multiple intelligent agents, creating a multifactor evaluation model for automation efficiency, and expanding integrations with other low-code and no-code platforms.