AI in Carbon Credit Integrating Artificial Intelligence in Sustainable Finance

Objective The purpose of this literature review is to investigate the potential integration of artificial intelligence (AI) into carbon credit markets, with the goal of understanding its revolutionary influence on emissions monitoring, trading efficiency, and environmental stewardship. The paper aims to explain how AI technologies can transform carbon markets by synthesising scholarly literature, reports, and case studies. Methodology This study uses an extensive literature review methodology to examine the role of AI in carbon credit markets. It combines information from a variety of sources, including scientific articles, reports, and case studies. The assessment includes an examination of AI-driven solutions such as analytics, machine learning algorithms, and predictive modelling for optimising emission reduction programmes and automating compliance monitoring processes. It also investigates the possibilities of AI tools such as natural language processing (NLP) and blockchain technology to promote innovation, market participation, and liquidity in carbon trading. Findings The findings indicate that AI has tremendous potential to improve the efficiency and transparency of carbon credit markets. Key discoveries show that AI technology can improve operations, reduce risk, and promote the development of financial products in carbon markets. Furthermore, AI-driven solutions enable stakeholders to negotiate complex regulatory frameworks and meet carbon reduction goals more effectively. The incorporation of AI has been shown to hasten the transition to a low-carbon economy by enhancing market participation and liquidity. Originality This study adds to the existing literature by emphasising AI's transformational potential in carbon credit markets. It emphasises the importance of AI technology in supporting sustainability, innovation, and resilience in financial ecosystems. Furthermore, the paper covers growing issues such as data privacy concerns, algorithmic biases, and legal difficulties surrounding the use of AI in carbon trading. It encourages governments, industry stakeholders, and AI developers to work together to define ethical norms and assure responsible AI use in order to achieve sustainable development goals.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-09
DOI
https://doi.org/10.5281/zenodo.14620984
Primary Topic
Sustainable Finance and Green Bonds
Type
article
Field-Weighted Citation Impact
0.00
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article

AI in Carbon Credit Integrating Artificial Intelligence in Sustainable Finance

Zenodo (CERN European Organization for Nuclear Research)
Sustainable Finance and Green Bonds
article

AI in Carbon Credit Integrating Artificial Intelligence in Sustainable Finance

article en

Abstract

Objective The purpose of this literature review is to investigate the potential integration of artificial intelligence (AI) into carbon credit markets, with the goal of understanding its revolutionary influence on emissions monitoring, trading efficiency, and environmental stewardship. The paper aims to explain how AI technologies can transform carbon markets by synthesising scholarly literature, reports, and case studies. Methodology This study uses an extensive literature review methodology to examine the role of AI in carbon credit markets. It combines information from a variety of sources, including scientific articles, reports, and case studies. The assessment includes an examination of AI-driven solutions such as analytics, machine learning algorithms, and predictive modelling for optimising emission reduction programmes and automating compliance monitoring processes. It also investigates the possibilities of AI tools such as natural language processing (NLP) and blockchain technology to promote innovation, market participation, and liquidity in carbon trading. Findings The findings indicate that AI has tremendous potential to improve the efficiency and transparency of carbon credit markets. Key discoveries show that AI technology can improve operations, reduce risk, and promote the development of financial products in carbon markets. Furthermore, AI-driven solutions enable stakeholders to negotiate complex regulatory frameworks and meet carbon reduction goals more effectively. The incorporation of AI has been shown to hasten the transition to a low-carbon economy by enhancing market participation and liquidity. Originality This study adds to the existing literature by emphasising AI's transformational potential in carbon credit markets. It emphasises the importance of AI technology in supporting sustainability, innovation, and resilience in financial ecosystems. Furthermore, the paper covers growing issues such as data privacy concerns, algorithmic biases, and legal difficulties surrounding the use of AI in carbon trading. It encourages governments, industry stakeholders, and AI developers to work together to define ethical norms and assure responsible AI use in order to achieve sustainable development goals.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 48%
Sustainable Finance and Green Bonds
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