UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 12 Issue 6
June-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2506743


Registration ID:
563307

Page Number

h324-h342

Share This Article


Jetir RMS

Title

AI-Driven Sustainability Intelligence: Enhancing Carbon Footprint Visibility Across IT Supply Chains

Abstract

The growing emphasis on sustainability has led other institutions to focus heavily on their carbon footprints across complex IT supply chains. This study delves into the question of how AI technologies are being employed in sustainability intelligence systems to ensure carbon footprint visibility along IT supply chains. What this work attempts to shed some light on is how AI solutions set to redefine or transform traditional methods of carbon accounting into newer methods of real-time monitoring, through a mix of qualitative insights and quantitative studies. The study analyzes data gathered from 250 IT companies working with AI-powered sustainability intelligence platforms to analyze their performance in reduction of carbon footprints, supply chain transparency, and operational efficiency. The statistical analysis run in SPSS showed a significant positive correlation between implementations of AI and improvements in carbon footprint visibility (r =0.742, p 0.001). The results indicate that organizations that have adopted AI-based sustainability intelligence systems noted a 34.7% improvement in the visibility of carbon footprints and a 28.3% improvement in overall emissions compared with the baseline levels of visibility and emission reductions that traditional approaches could offer. Consequently, this investigation will augment the current body of knowledge in digital solutions for sustainability while also preparing firms for some practical insights to pursue improve.

Key Words

Artificial Intelligence, Sustainability Intelligence, Carbon Footprint, IT Supply Chain, Environmental Monitoring, Digital Transformation

Cite This Article

"AI-Driven Sustainability Intelligence: Enhancing Carbon Footprint Visibility Across IT Supply Chains", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.h324-h342, June-2025, Available :http://www.jetir.org/papers/JETIR2506743.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"AI-Driven Sustainability Intelligence: Enhancing Carbon Footprint Visibility Across IT Supply Chains", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. pph324-h342, June-2025, Available at : http://www.jetir.org/papers/JETIR2506743.pdf

Publication Details

Published Paper ID: JETIR2506743
Registration ID: 563307
Published In: Volume 12 | Issue 6 | Year June-2025
DOI (Digital Object Identifier):
Page No: h324-h342
Country: Pune, Maharashtra, India .
Area: Management
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

000101

Print This Page

Current Call For Paper

Jetir RMS