Sustainability And Green IT: Green Cloud Computing, AI For Energy Optimization, And Carbon Aware Software Development

This journal was originally published via IOSR and explores how the rapid expansion of digital infrastructure has intensified global energy consumption, placing significant pressure on environmental sustainability. This study investigates the role of green cloud computing, artificial intelligence (AI) for energy optimization, and carbon-aware software development in reducing the environmental footprint of IT operations. Using a mixed-method approach, primary data were collected through surveys of IT professionals and secondary data from sustainability reports, focusing on key performance indicators such as Power Usage Effectiveness (PUE), Carbon Usage Effectiveness (CUE), and Energy Reuse Effectiveness (ERE). Results indicate measurable improvements in energy efficiency and carbon reduction among organizations that integrate renewable energy sources, AI-driven workload management, and sustainability-focused software practices. AI-enabled optimization demonstrated the most significant impact, enabling dynamic resource allocation, predictive cooling, and energy-aware scheduling. However, barriers such as high initial investment, uneven access to renewable energy infrastructure, and a lack of standardized sustainability metrics remain. The study concludes that sustainable IT practices are both technically feasible and economically advantageous but require coordinated policy support, industry-wide metric standardization, and skills development to achieve large-scale adoption. These findings contribute to the growing discourse on environmentally responsible digital transformation, offering actionable strategies for aligning IT growth with global climate goals.<br><b>This journal was originally published via IOSR. For citation, please refer to the original DOI:</b> https://doi.org/10.9790/0661-2704044459<b>Version note:</b> This is a postprint/archive version uploaded for open access purposes. No changes have been made to the core content.