SUSTAINABLE INFORMATION RESOURCE MANAGEMENT: A FRAMEWORK FOR MITIGATING THE CARBON FOOTPRINT OF AI-DRIVEN CLOUD INFRASTRUCTURE.

Abstract

The rapid proliferation of Artificial Intelligence (AI) and high-performance cloud computing has
created a critical tension between technological advancement and environmental sustainability. While
AI offers transformative potential for organizational efficiency, its "hidden" environmental costs—
driven by massive electricity consumption, water-intensive cooling, and electronic waste—threaten
global net-zero objectives. This paper addresses a significant research gap in the field of Information
Resources Management (IRM), where traditional frameworks prioritize data accessibility and security
while largely ignoring the carbon intensity of digital assets. The study proposes a novel framework for
Sustainable Information Resource Management (SIRM) that integrates "Green ICT" principles into
standard data lifecycles, built upon four pillars: selective data ingestion (Green Pruning), carbonaware
workload scheduling, algorithmic efficiency (the Principle of Least Compute), and circular
hardware management. To validate this model, a mixed-methods quantitative simulation was
conducted, indicating that the implementation of the SIRM framework can reduce net carbon emissions by up to 40% and lower total energy consumption by 25% without significant degradation to
operational latency. The findings introduce the Total Carbon Cost of Information (TCCI) as a new
metric for corporate ESG reporting, shifting the role of the IT manager from a service provider to a
resource steward and concluding that decoupling digital growth from environmental impact is a
strategic necessity for the future of the global digital economy.