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Journal . 2026
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
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ACCELERATE SUSTAINABILITY WITH AI: EMBRACING INNOVATION FOR A BETTER WORLD

Authors: Asst. Prof. Pranjal Potdar;

ACCELERATE SUSTAINABILITY WITH AI: EMBRACING INNOVATION FOR A BETTER WORLD

Abstract

Artificial intelligence (AI) is rapidly becoming a game-changing tool for tackling global environmental issues. The purpose of this research is to explore how Artificial Intelligence can be applied to drive advance sustainability enterprise across diverse sectors. For instance, numerous associations are formerly tapping into AI technologies to enhance energy effectiveness. By incorporating AI into sustainability systems and processes, associations can optimize resource application, reduce waste, and save energy and capitalist. An illustration of this is smart grids, where AI-powered algorithms can play a transformative part in revolutionizing energy operation. The methodologies for accelerating sustainability with AI involve relating and assaying sustainability challenges, developing AI results, enforcing AI results, monitoring and assessing issues, conforming and perfecting. AI is reshaping sustainability attempts by allowing associations to minimize operations, reduce waste and accelerate the adoption of low-carbon technologies. By integrating AI into sustainability initiatives, companies can improve efficiency and foster new business models that align environmental responsibility with economic growth. An association between AI and sustainability is not only perfecting effectiveness but also creating new openings for invention. From energy operation to agriculture and climate monitoring, AI is proving to be an important tool in the fight against environmental challenges. As we look to the future, it is clear that AI will play a vital part in creating a more sustainable and adaptable world.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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