Ershova Anna Dmitrievna, Student, Department of Information Technologies and Control Systems, Ural Federal University named after the first President of Russia B.N. Yeltsin
Abstract
This paper presents a critical analysis of the limitations of two key decision support tools in digital project management ecosystems: heterogeneous data integration architectures and digital twin technology. Based on a systematic review of publications and documented case studies (2020–2025), we demonstrate that the primary cause of widespread implementation failures is not technological immaturity but a systemic gap between technological potential and organizational readiness. Four major barriers are identified: semantic gaps in integration, data lake degradation into “data swamps,” opacity of AI algorithms, and organizational resistance. Practice-oriented recommendations are provided for shifting implementation priorities from tools to data governance, model explainability, and organizational culture development.
KEYWORDS: digital ecosystem, project management, data architecture, project digital twin, systems integration, artificial intelligence, semantic integration, data quality.
Download article DECISION-MAKING METHODS IN DIGITAL PROJECT MANAGEMENT ECOSYSTEMS USING ANALYTICS AND AI
