The Environmental Footprint of Artificial Intelligence: Balancing Technological Progress with Energy Efficiency and Sustainability

Deblina Sarkar

The Environmental Footprint of Artificial Intelligence: Balancing Technological Progress with Energy Efficiency and Sustainability

Author(s)	Deblina Sarkar
Country	United States
Abstract	Artificial Intelligence (AI) has emerged as a transformative technology with applications across healthcare, finance, education, manufacturing, transportation, scientific research, and public administration. The rapid expansion of AI, particularly computationally intensive machine-learning and generative AI systems, has also generated growing concerns regarding energy consumption, greenhouse-gas emissions, water use, electronic waste, and the broader environmental footprint of digital infrastructure. This paper examines the environmental implications of AI and explores strategies for balancing technological progress with energy efficiency and sustainability. A qualitative and conceptual research methodology is adopted through an analysis of literature concerning AI, data centres, energy consumption, sustainable computing, machine learning, renewable energy, and environmental management. The study identifies model training, inference, data-centre operations, cooling systems, semiconductor manufacturing, and hardware disposal as important components of AI's environmental footprint. The analysis further demonstrates that AI presents a dual challenge: while AI systems can increase energy demand and resource consumption, they can simultaneously support environmental sustainability through energy optimisation, climate modelling, smart grids, precision agriculture, intelligent transportation, and resource management. The paper proposes a Sustainable AI Framework based on energy-efficient algorithms, hardware optimisation, renewable electricity, efficient cooling, carbon-aware computing, responsible model deployment, lifecycle management, and transparent environmental reporting. The study concludes that sustainable AI requires a lifecycle perspective in which technological performance is evaluated alongside energy efficiency, carbon emissions, water consumption, resource use, and social responsibility.
Keywords	Artificial Intelligence, Environmental Sustainability, Sustainable AI, Energy Efficiency, Data Centres, Green Computing, Carbon Emissions, Renewable Energy, Electronic Waste, Green AI.
Field	Engineering
Published In	Volume 5, Issue 2, March-April 2023
Published On	2023-04-30

View / Download PDF File

About AJAMRI Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+1-872-302-3851	editor@ajamri.com

American Journal of Advanced Multidisciplinary Research and Innovation

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

The Environmental Footprint of Artificial Intelligence: Balancing Technological Progress with Energy Efficiency and Sustainability

Share this