IMPROVING TASK COMPLETION PREDICTABILITY AND WORK VISIBILITY IN OUTSOURCED IT PROJECTS USING PROCESS FORMALIZATION AND AI – ASSISTED COMMUNICATION AUTOMATION
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Date
2026
Authors
Diak, Petro
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Journal ISSN
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Publisher
Manuscript
Abstract
Outsourced IT projects often suffer from unpredictable task completion, limited real-time visibility, and coordination inefficiencies caused by inconsistent status updates and fragmented communication. In the studied environment, Data Engineers and QA engineers update work items in Azure DevOps irregularly, follow individual reporting routines, and frequently communicate via ad hoc messages in Microsoft Teams. As a result, task boards do not reflect the actual state of work, architects and leads are overloaded with coordination tasks, and project managers lack timely information for decision-making. This reduces delivery predictability and erodes client confidence.
This Capstone addresses these issues by developing a Task Visibility and Predictability Framework that combines process formalization with AI-assisted communication automation. Using qualitative methods and semi-structured interviews, the study applies open and axial coding to identify causes of visibility breakdowns and coordination overload. Based on Agile governance and project-management practices, the framework establishes clear reporting responsibilities, standardized update routines, and structured communication rules.
The framework introduces formal update triggers, minimal documentation standards, and role-specific responsibilities. It also incorporates lightweight AI-assisted mechanisms—such as reminders, stale-task detection, and Azure DevOps–Microsoft Teams integration—to support timely updates without relying on complex models or large datasets.
Its application shows improved task visibility, fewer outdated task states, reduced need for status meetings, and lower coordination burden. The findings suggest that even simple automation, when aligned with clear processes, can significantly enhance transparency, predictability, and execution reliability in outsourced IT projects.
Description
Keywords
task visibility, Azure DevOps, qualitative analysis, AI-assisted automation, outsourced IT projects, coordination overload
Citation
Diak, P. (2026). IMPROVING TASK COMPLETION PREDICTABILITY AND WORK VISIBILITY IN OUTSOURCED IT PROJECTS USING PROCESS FORMALIZATION AND AI – ASSISTED COMMUNICATION AUTOMATION. Kyiv: American University Kyiv. URI: https://er.auk.edu.ua/handle/234907866/178