Authors :
Sakera Begum
Volume/Issue :
Volume 10 - 2025, Issue 7 - July
Google Scholar :
https://tinyurl.com/y2jb2yvz
Scribd :
https://tinyurl.com/5dc7rx3r
DOI :
https://doi.org/10.38124/ijisrt/25jul1726
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Small and medium-sized enterprises (SMEs) are highly vulnerable to economic crises due to financial
constraints and operational instability. The COVID-19 pandemic has exacerbated these vulnerabilities, emphasizing the
need for robust financial systems. AI can help enhance resilience and financial sustainability. The purpose of this review
study is to investigate how AI-driven predictive financial modelling can enable SMEs in the United States to maintain
economic resilience in the aftermath of a pandemic. The findings show that AI adoption leads to considerable gains in
financial decision-making, early risk detection, and resource optimization all of which are critical components of
resilience. Predictive models may anticipate cash flow, evaluate credit risk, and provide SMEs with timely insights into
market trends. However, challenges such as data quality and a lack of digital infrastructure may impede adoption,
especially among resource-constrained or low-tech businesses. Therefore, predictive financial modelling powered by AI
has transformative potential for increasing the resilience and competitiveness of United States SMEs in a dynamic and
constantly developing economy.
Keywords :
Algorithmic Decision-Making, AI-Driven Financial Forecasting, Data Analytics, Business Support, Economic Impact.
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Small and medium-sized enterprises (SMEs) are highly vulnerable to economic crises due to financial
constraints and operational instability. The COVID-19 pandemic has exacerbated these vulnerabilities, emphasizing the
need for robust financial systems. AI can help enhance resilience and financial sustainability. The purpose of this review
study is to investigate how AI-driven predictive financial modelling can enable SMEs in the United States to maintain
economic resilience in the aftermath of a pandemic. The findings show that AI adoption leads to considerable gains in
financial decision-making, early risk detection, and resource optimization all of which are critical components of
resilience. Predictive models may anticipate cash flow, evaluate credit risk, and provide SMEs with timely insights into
market trends. However, challenges such as data quality and a lack of digital infrastructure may impede adoption,
especially among resource-constrained or low-tech businesses. Therefore, predictive financial modelling powered by AI
has transformative potential for increasing the resilience and competitiveness of United States SMEs in a dynamic and
constantly developing economy.
Keywords :
Algorithmic Decision-Making, AI-Driven Financial Forecasting, Data Analytics, Business Support, Economic Impact.