In most recent time, the global landscape of supply chain management has experienced unprecedented challenges during the COVID-19 pandemic, which has significantly impacted the routine and smooth operations of different firms in the United States. This paper explains about the importance of artificial intelligence (AI) and machine learning (ML) in the mitigation of these disruptions and possible ways of improving supply chain security and its efficiency. This research adopted a questionnaire survey involving 281 managers, with the aim to comprehensively examine the current state of AI integration across the US supply chain sector, with focus on some key components like real-time tracking, cost optimization, and risk management. A mixed method approach was adopted for this research, utilizing both inferential and descriptive analyses to unravel insights and trends into the role of AI in enhancing supply chain security. The results indicate that integrating AI, most especially through cost optimization, real-time tracking, and risk management components, emerges as a significant determinant of supply chain security in the United States. Real-time tracking technologies are identified as crucial for monitoring shipments and assets, enabling quick responses to security incidents, and ensuring end-to-end visibility throughout the supply chain. Despite the potential benefits, the study highlights challenges that hinder the widespread integration of AI technologies in the US supply chain. The high cost of AI adoption and the limited availability of skilled personnel are major obstacles. To address these challenges, the paper proposes practical recommendations. Firstly, real-time tracking technologies are recommended to monitor shipments and assets, facilitating rapid responses to security incidents, and ensuring visibility across the entire supply chain. Furthermore, the paper suggests optimizing costs by investing in cost-effective security solutions. This includes leveraging AI for automated monitoring systems and adopting secure packaging measures. These strategies aim to minimize vulnerabilities without compromising security standards, offering a balanced approach to enhancing supply chain security while mitigating the financial implications associated with AI adoption.