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Contributor
Ajaya Swain
Digital Publisher
Digital Commons at St. Mary's University
Publication Date
Spring 2025
Keywords
Tariffs; Auto parts; International trading; AI applications; Supply chains
Description
U.S. tariffs (7.5-25%) on auto parts from China, Canada, and Mexico are severely disrupting the automotive industry, a key global economic driver. These tariffs dramatically increase production costs and vehicle prices, potentially by up to $12,200 per vehicle (CBS News, 2025; MarketWatch, 2025). These tariffs necessitate major supply chain adjustments, leading to inefficiencies (MIT Sloan, 2024). Supplier diversification, while intended to mitigate tariff impact, extends lead times and shrinks profit margins (XenonStack, 2025). The industry's complex supplier network is now highly vulnerable, compelling companies to seek more adaptable strategies. AI-driven technologies like predictive analytics and route optimization offer potential solutions to these disruptions (RTS Labs, 2023). Real-time logistics and demand forecasting via AI can reduce costs by up to 15% and improve inventory accuracy by 20% (XenonStack, 2025). However, high implementation costs remain a significant obstacle (Deloitte, 2024)
Format
Size
1 page
City
San Antonio, Texas
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
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Other Computer Engineering Commons, Public Affairs, Public Policy and Public Administration Commons
