One of the primary challenges in accurately assessing and reducing greenhouse gas emissions lies in the lack of comprehensive and standardized reporting. Many companies are not obligated to disclose emissions beyond scope 1, resulting in significant gaps in emissions data. Permutable AI’s project bridges this gap by leveraging its expertise in natural language processing and data science to predict and estimate emissions across scopes 1, 2, and 3, offering a holistic view of companies’ carbon footprints.
Precise predictions of corporate emissions have far-reaching implications for stakeholders across the supply chain industry. The development of effective climate policies and regulations relies on accurate emission data, enabling the implementation of measures to mitigate climate change.
By leveraging accurate emissions predictions, companies driven by a sense of corporate responsibility can set reduction targets, track progress, and showcase their commitment to sustainability. Investors can also benefit from reliable emissions predictions, enabling them to make informed decisions and assess the sustainability of potential investments. Furthermore, accurate predictions support effective climate risk management, enabling companies to identify and address climate change-related risks.
The project’s results have already showcased the superiority of machine learning models over traditional statistical methods in predicting emissions. Permutable AI’s machine learning models demonstrated remarkable accuracy improvements, ranging from 68% to 99%, compared to using country averages. These results underscore the potential of machine learning techniques in estimating carbon emissions with relatively limited data.
Benefits for companies in practical applications of Permutable AI’s project include:
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Higher accuracy in determining supply chain carbon evaluations
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Enhancing sustainability reporting and simplified carbon evaluation
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Supply chain optimization
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Sustainable procurement decisions
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Benchmarking and industry comparisons
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Stakeholder engagement and transparency around corporate net zero strategies
These use cases demonstrate the practical value of Permutable’s project in driving sustainability, optimizing supply chains, and facilitating informed decision-making within the supply chain industry.
Permutable AI’s CEO and Founder, Wilson Chan, expressed his excitement for the groundbreaking project. He stated, ‘Our mission at Permutable is to pave the way for a sustainable future by enhancing the accuracy and transparency of carbon emissions data. With our expertise in AI-driven sustainability solutions, we are addressing the critical need for reliable emissions reporting in the supply chain sector.’
Permutable is currently in the process of developing a prototype app that harnesses the power of their advanced machine learning algorithms and natural language processing technology to revolutionize carbon emission predictions for a sustainable future. This app aims to provide businesses with a user-friendly tool to accurately assess and track their carbon emissions across scopes 1, 2, and 3, enabling them to make data-driven decisions towards reducing their environmental impact.
Permutable AI recognizes the importance of collaboration and engagement with interested parties in refining and tailoring the app to meet specific industry needs. They welcome input from businesses, sustainability professionals, supply chain experts, and other stakeholders who are passionate about driving positive change and achieving sustainability goals.
If you are interested in learning more about the prototype app or would like to participate in the development process, please get in touch with Permutable. They are eager to collaborate, gather feedback, and ensure that the app delivers practical solutions for carbon emissions management in supply chains.
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To express your interest or enquire further about the prototype app, please reach out to [email protected]
Media Contact
Company Name: Permutable AI
Contact Person: Talya
Email: Send Email
Phone: +447593948184
Country: United Kingdom
Website: https://www.permutable.ai
