This article presents a methodology for modeling the impact of internal and external environmental carbon emission factors on the resulting indicators of an international company. The research uses picture fuzzy rough sets to model the impact of factors on the resulting indicators. The proposed model is based on a dataset that includes the company's profit, revenue, valuation, share price, and market share from 2012 through 2022. The study proposes a framework for understanding the complex relationship between carbon emissions, economic factors, and the performance of international companies. The research discusses the challenges and opportunities for international companies in the context of climate change and technological innovation. The study also explores the impact of carbon policies on international companies, highlighting increased production costs and the need for investment in clean technologies. Additionally, the research examines the role of artificial intelligence in improving the efficiency and sustainability of international companies through logistics optimization, predictive maintenance, and demand forecasting. The results show that the proposed model can assess the impact of internal and external environmental factors on the resulting indicators of an international company. The study concludes that the model provides a valuable tool for companies and policymakers to understand the complex interplay between internal and external factors, carbon emissions, and economic performance. The authors recommend further research to refine the model and validate its accuracy in diverse contexts.This article presents a methodology for modeling the impact of internal and external environmental carbon emission factors on the resulting indicators of an international company. The research uses picture fuzzy rough sets to model the impact of factors on the resulting indicators. The proposed model is based on a dataset that includes the company's profit, revenue, valuation, share price, and market share from 2012 through 2022. The study proposes a framework for understanding the complex relationship between carbon emissions, economic factors, and the performance of international companies. The research discusses the challenges and opportunities for international companies in the context of climate change and technological innovation. The study also explores the impact of carbon policies on international companies, highlighting increased production costs and the need for investment in clean technologies. Additionally, the research examines the role of artificial intelligence in improving the efficiency and sustainability of international companies through logistics optimization, predictive maintenance, and demand forecasting. The results show that the proposed model can assess the impact of internal and external environmental factors on the resulting indicators of an international company. The study concludes that the model provides a valuable tool for companies and policymakers to understand the complex interplay between internal and external factors, carbon emissions, and economic performance. The authors recommend further research to refine the model and validate its accuracy in diverse contexts.