Paper Details

Name: Anisha Chaurasia, Bikasdev Chhura & Jyoti
Country: India

Year: 2025
Volume: Volume No: 12, Issue No: 2, Year: 2025, (Specials issue-1)
Page Number: 92-103
DOI: https://doi.org/10.5281/zenodo.17839220

ABSTRACT
As the global climate emergency is escalating, the need for novel and adaptive, evidencebased solutions to lessen detrimental impacts on our environment, and build climate
resilience is more pressing than ever before. Artificial Intelligence (AI) is being seen as an
active player to reshape the way we identify, monitor, and act on environmental challenges.
This paper investigates the different ways AI can help us respond to the climate and
ecological crisis, focusing on specific applications of AI in several prominent sectors,
including agriculture, air and water quality, disaster forecasting and preparedness, renewable
energy, and biodiversity protection and conservation.
Using a qualitative approach primarily based on secondary data from global reports, peerreviewed literature, and international agency databases, this study further analyzes some realworld case studies to highlight how AI is being used in practice for improved environmental
sustainability. Example case studies considered included: Google's AI-based flood forecast
system for India, Microsoft's AI-based smart farming projects, Global Forest Watch tracking
global deforestation using machine learning, etc. These case study examples illustrate how AI
can better predictions, make better use of resources and help to make timely decisions for
managing environmental systems.
While the findings from this analysis show that AI can add considerably to climate adaptation
and mitigation strategies, it is fundamentally important that equitable access to data and/or
data collection, ethical processes, and cooperative policy frameworks are in place involving
local capabilities. It is important to deal with other problems like algorithmic biases, resource
use in processing (energy intensive), and access inequities in marginalized, developing
contexts so that the use of AI is responsible and sustainable. The study ends by calling for
better coordination from across stakeholder categories, including governments, technology
companies, and environmental organizations towards developing an approach for responsible
AI. It further recommends improving the open data infrastructure, embedding AI in climate
governance, and an assurance that technology continues to keep up with aims of
environmental justice.
Keywords: Artificial Intelligence, Climate Change, Environmental Sustainability, Case
Studies, Secondary Data, Smart Technologies, Green Innovation, Climate Governance