Bolanle Pamilerin, Damilare (2025) GREEN SOFTWARE ENGINEERING: IMPLEMENTING AI AND CLOUD-NATIVE SOLUTIONS FOR SUSTAINABLE IT PRACTICES. Manuscripts on the Artificial Intelligence and Digital Research, 2 (8). pp. 78-92. ISSN 3064-8807

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Abstract

The rapid expansion of information technology (IT) and software systems has contributed significantly to global energy consumption and carbon emissions, with data centers alone accounting for nearly 1–1.5% of worldwide electricity use. In response to these growing environmental concerns, Green Software Engineering (GSE) has emerged as a discipline dedicated to designing and developing software that minimizes its ecological footprint while maintaining efficiency and scalability. This article explores how Artificial Intelligence (AI) and cloud-native solutions serve as enablers of sustainable IT practices. AI enhances energy optimization through intelligent workload scheduling, predictive analytics, and carbon-aware software operations, while cloud-native architectures—built on containerization, microservices, and serverless computing—support dynamic scalability and efficient resource utilization. We highlight the key contributions of GSE in reducing emissions, improving operational efficiency, and aligning IT strategies with global sustainability goals. At the same time, the paper critically examines challenges, including the risks of AI model energy intensity, data privacy concerns, and integration complexities in legacy systems. Finally, we present future directions that include carbon-aware software design patterns, AI-driven sustainability dashboards, and industry-wide adoption of green metrics. By combining AI and cloud-native technologies within the GSE framework, organizations can accelerate the transition toward environmentally sustainable and responsible IT ecosystems.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	26 Sep 2025 11:16
Last Modified:	26 Sep 2025 11:16
URI:	http://eprints.umsida.ac.id/id/eprint/16380

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