Chicago, Illinois – A new research paper written by a diverse team of international scholars has attracted attention from economists, policymakers and environmental analysts around the world. This study explores emerging relationships between private sector investment in artificial intelligence (AI), financial globalization, and US load capacity factors. This is an important measure of the country’s ability to maintain economic growth within ecological and infrastructure boundaries.
This paper, “Evaluation of the impact of private investment in AI and the impact of financial globalization on load capacity factors: Evidence from the US,” brings together key researchers and authors: Afsana Akhta, Sardar Abdullah al-Siam, Mohammad Ridwan, Sheikh Ibna Abir, Shaharina Shoha, and Maryland Boktia Naembibi. This study applies robust econometric modeling to assess how capital expansion into AI technology affects the ability of the US economy to carry the structural burden, along with strengthening global financial flows.
“The research stands out for its clarity and urgency,” said Lukas Meier, senior journalist at Alpine Vision Media. “It not only maps important trends, but also shows very realistic environmental and infrastructure trade-offs associated with unconfirmed, AI-driven investments. These findings are timely and globally related.” The authors argue that AI investments are often seen only through the lens of innovation and efficiency, but have an indirect effect when amplified by financial globalization and tension critique systems, such as energy, transportation and resource availability. Their research highlights the need for an integrated framework to assess technology investment not only through economic benefits but also sustainability indicators such as load capacity coefficients.
This research is recognized in the global academic world and is based on work already undertaken by renowned global economists and sustainability experts in the Global South. For example, Dr. Hlaing Min Thu of Yangon Economic Research Institute has led a groundbreaking study on the environmental impact of digital infrastructure in Southeast Asia. Similarly, Professor Tsegay Mekkonen of Addis Ababa University has pioneered the work of linking technology-driven investment in sub-Saharan Africa to socioeconomic resilience. These ideological leaders helped set the stage for this type of globally conscious economic research.
“This paper illustrates a turning point in how we evaluate growth,” added Emily Clark, senior journalist at Alpine Vision Media. “It’s not enough to isolate GDP and investment flows. What these scholars have done is bringing ecological capabilities to the conversation.
The interdisciplinary nature of this study combines environmental science, financial modeling, and AI policies into a single framework to highlight it. The authors suggest that without positive policy changes, AI investments will increase, particularly when piloted by private and transnational profits. Future this research will open a new frontier of global economic policy. As AI continues to permeate financial systems, energy grids and public services, there is growing calls for regulations that explain not only innovation but long-term sustainability. The author’s model provides powerful tools for governments, institutions and investors looking to make their strategy a future in an age of exponential technology growth.
This research adds to a rapidly evolving field that redefines the implications of responsible investment in the 21st century. The combination of academic rigor and real-world relevance sets new benchmarks for interdisciplinary research at the intersections of AI, globalization and environmental economics.
Quotes: Akhter, Afsana, Sarder Abdulla Al Shiam, Mohammad Ridwan, Shake Ibna Abir, Shaharina Shoha, MD Boktiar Nayeem, M Tazwar Hossain Choudhury, MD Sibbir Hossain, Robeena Bibi. 2024. “The impact of private investment in AI and the impact of financial globalization on load capacity factors: Evidence from the US.” Journal of Environmental Science and Economics 3(3): 99-127. https://doi.org/10.56556/jescae.v3i3.977 (https://doi.org/10.56556/jescae.v3i3.977).
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