Leveraging Blockchain, Artificial Intelligence, and Data Analytics for Sustainable and Transparent Resource Management

Abstract

The rising complexity in current resource management projects has generated demand for transparent, efficient, and sustainable operational systems. Current research work focuses on identifying the importance of Blockchain, Artificial Intelligence, and Data Analytics in improving transparency, efficiency, and sustainability in resource management projects from 2018 to 2025. Quantitative research methodology was adopted for analysis, incorporating a structured data pool with 1,200 projects in ten geographic regions and eight different resource management types. Indexes such as Transparency Index, Emission Reduction, Budget, Data Volume, and Project Duration were assessed for analysis with Python-based analysis tools. This research evaluated individual and collective impact of Blockchain and AI adoption on project performance. The result shows that adoption of Blockchain technology leads to improved transparency, while adoption of AI improves sustainability performance, specifically in emission reduction. Joint adoption of Blockchain and AI showed best overall performance in projects, although with enhanced financial, processing, and timeline costs. Visualization techniques such as scatter plots and box plots identified correlations regarding impact levels in data size, transparency, and performance, emphasizing importance in having overall technology systems. These findings indicate that the combined use of Blockchain, AI, and analysis is resulting in more responsible and data-driven resource management. At the same time, there is an increase in costs for implementation, coupled with extended project schedules. It is proposed to embrace overall digital architectures, skill development in information technology, and policy initiatives in support of data transparency for achievement in resource management. On the whole, there emerges experimental validation in support of strategic integration for efficient, transparent, and sustainable resource management outcomes.