Artificial Intelligence and Economic Resilience: A Review of Predictive Financial Modelling for Post-Pandemic Recovery in the United States SME Sector

TLDR

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, which has transformative potential for increasing the resilience and competitiveness of United States SMEs.

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.