Volume 17, Number 4

AI-Driven Strategies of Mitigating Cybersecurity Threats in U.S. Small and Medium Enterprises (SMEs)

  Authors

Kemisola Kasali ¹, Precious Orekha ², Oluwaseun John Bamigboye ³, Afolabi Sabur Ajao ⁴, Peter O. Alawiye ⁵, Adeola Noheemot Raji ⁶, ¹ University of Arkansas at Little Rock, USA, ² Drexel University, USA, ³ California Miramar University, USA, ⁴ Northwestern University, USA, ⁵ New Mexico Highlands University, USA, ⁶ University of New Haven, USA<

  Abstract

Small and Medium Enterprises (SMEs) in the United States face escalating cybersecurity threats including phishing, ransomware, and data breaches, yet lack resources for robust defense mechanisms. This qualitative exploratory research employs thematic content analysis of secondary data from peer-reviewed academic literature, industry reports from NIST and OECD, and documented case studies to examine AIdriven cybersecurity strategies for SMEs. The study identifies cost and lack of expertise as primary AI adoption barriers, with retail and financial services demonstrating higher adoption levels compared to manufacturing and education. A structured three-component framework focusing on threat detection, response automation, and compliance monitoring is developed for resource-constrained SME environments. Findings reveal critical gaps in SME-specific AI frameworks, with healthcare, retail, and financial services sectors showing vulnerability to cyberattacks and potential cyber resilience improvement. The research concludes that scalable AI methodologies tailored for smaller businesses and public-private collaboration are essential to strengthen cyber defenses across this vulnerable sector, addressing implementation costs and skilled personnel requirements.

  Keywords

Cybersecurity, SMEs, Artificial Intelligence, Threat Detection, Predictive Analytics.