Evaluating The Application of AI to Enhance The US Government's Screening of Foreign Investments for National Security Risks

Foreign Direct Investment (FDI) is critical in driving economic growth, increased technological innovation, and interdependence in the globe.With foreign investments growing to concentrate on strategic industries like defense, artificial intelligence, telecommunications and energy, they present sophisticated challenges to national security. The Committee on Foreign Investment in the United States (CFIUS) has kept the United States at the leading edge in protecting national interests by scrutinising foreign investments that could pose any security or technological independence. Even with the efficacy of this framework, the existing screening procedure is mostly reactive and manual in nature, and as such, it lacks the capability to respond to the dynamism and complexity of contemporary global investment. The study examines how Artificial Intelligence (AI) can be incorporated into the U.S. foreign investment screening system in an effort to enhance efficiency, accuracy, and predictability in high-risk transaction transactions. The research based on the OECD Foreign Direct Investment Aggregated Dataset as an empirical base examines the trends, tendencies, and abnormalities in foreign direct investment flows into the nation, specifically the flows in the direction of the United States. The conceptual application of the AI methods like anomaly detection, clustering, and predictive modeling to the investment data are used in order to interpret investment data and predict the possible risks. This study builds up a framework that shows the use of AI to automate data processing and increase transparency and offer early-warning systems that can help the CFIUS identify strategic or non-transparent investments. The paper concludes that AI application in the process of foreign investment screening would allow the U.S government to stop doing the assessment reactive and instead make decisions based on intelligence. It highlights the need to govern AI ethically, share data among agencies, and train the system in order to ensure accountability and integrity of national security. The results add to the increasing overlap between technology and policy by demonstrating how AI can redefine investment control to form a more responsive and data-driven and future-oriented security tool.