Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2582-8185 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

AI-enhanced scenario planning for U.S. food trade policy: Anticipating global supply chain shocks and food insecurity risks

Breadcrumb

  • Home
  • AI-enhanced scenario planning for U.S. food trade policy: Anticipating global supply chain shocks and food insecurity risks

Obunadike Thank God Chiamaka 1, * and Adedapo Alawode 2

1 Food Economics and Trade, Poznan University of Life Sciences, Poznan, Poland.

2 Department of Agricultural Economics and Agribusiness, New Mexico State University, USA.

Research Article

World Journal of Advanced Research and Reviews, 2025, 26(02), 943-962

Article DOI: 10.30574/wjarr.2025.26.2.1786

DOI url: https://doi.org/10.30574/wjarr.2025.26.2.1786

Received on 31 March 2025; revised on 06 May 2025; accepted on 09 May 2025

The increasing frequency of global supply chain disruptions—exacerbated by pandemics, geopolitical tensions, climate-related events, and economic volatility—has exposed critical vulnerabilities in U.S. food trade policy. As the United States navigates complex interdependencies in agricultural imports and exports, traditional scenario planning methods often fall short in addressing the velocity and uncertainty of modern supply chain shocks. To strengthen national food security and resilience, there is an urgent need for intelligent, data-driven frameworks that can anticipate risks and support proactive policy formulation. This paper investigates the role of artificial intelligence (AI)-enhanced scenario planning in transforming U.S. food trade policy amid escalating global uncertainty. We present a multi-layered framework that integrates machine learning, agent-based modeling, and geospatial analytics to simulate diverse trade disruption scenarios—ranging from port closures and export bans to climate-induced yield losses. The proposed system leverages real-time data inputs such as trade flows, climate projections, and geopolitical signals to model cascading impacts across domestic supply chains and global food markets. Case studies illustrate how AI-enhanced tools can identify early warning signs, quantify ripple effects of trade policies, and optimize contingency strategies. Special focus is given to evaluating implications for low-income and food-insecure populations within the U.S., ensuring equitable outcomes in policy response. The study also discusses the importance of ethical AI governance, data transparency, and public-private collaboration in shaping responsive and inclusive food trade policy. In conclusion, AI-enhanced scenario planning offers a strategic imperative for safeguarding U.S. food systems against emergent threats, while fostering adaptive, forward-looking trade policy in an increasingly volatile global landscape.

AI Scenario Planning; Food Trade Policy; Supply Chain Shocks; Food Insecurity; U.S. Agriculture; Geopolitical Risk

https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-1786.pdf

Preview Article PDF

Obunadike Thank God Chiamaka and Adedapo Alawode. AI-enhanced scenario planning for U.S. food trade policy: Anticipating global supply chain shocks and food insecurity risks. World Journal of Advanced Research and Reviews, 2025, 26(2), 943-962. Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.1786

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 International Journal of Science and Research Archive - All rights reserved

Developed & Designed by VS Infosolution