An Integrated Cloud and Network-Aware AI Architecture for Optimizing Project Prioritization in Healthcare Strategic Portfolios

Geetha Nagarajan

doi:10.15662/IJRAI.2022.0501004

Authors

Geetha Nagarajan Department of Computer Science and Engineering, SAEC, Chennai, India Author

DOI:

https://doi.org/10.15662/IJRAI.2022.0501004

Keywords:

Cloud-enabled AI, Network-aware architecture, Healthcare portfolio management, Project prioritization, Strategic decision support, Machine learning analytics, Cloud–network integration

Abstract

Healthcare organizations increasingly face the challenge of selecting and prioritizing projects that align with strategic objectives while responding to dynamic clinical, operational, and technological demands. This study presents an integrated cloud-based and network-aware AI architecture designed to optimize project prioritization within healthcare strategic portfolios. The proposed framework leverages scalable cloud infrastructures, real-time network intelligence, and advanced machine learning models to evaluate project impacts, risks, dependencies, and resource constraints. By incorporating multi-criteria decision analytics, the architecture enhances transparency, accelerates decision cycles, and supports evidence-driven portfolio governance. A prototype implementation demonstrates how cloud elasticity, network performance monitoring, and AI-driven prioritization collectively improve alignment with organizational goals, reduce operational bottlenecks, and strengthen overall portfolio performance. The findings highlight the value of cloud–network synergy in enabling adaptive, data-driven project prioritization for modern healthcare enterprises.

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