Future-focused manufacturers are using artificial intelligence to proactively shift their supply chain strategy as tariffs disrupt global markets.
Tariffs used to be slow-moving, background considerations for organizations as they built forecasts and strategies for the supply chain. But over the past year, they have transformed into fast-changing macroeconomic factors with wide-reaching influence that demand continuous monitoring.
Absent a proactive strategy for tariff management, leaders risk being exposed. AI can help manufacturers adapt to this new reality, offering granular, up-to-the-minute analysis that carves a clear path through volatile markets and disrupted supply chains.
Since the America First Trade Policy Memorandum was announced in January, there have been nearly 90 notable tariff announcements affecting international trade. Most originated from within the U.S., although retaliatory actions by Canada, China and the European Union have added yet more complexity to the landscape. Many of these tariffs are changing shape from week to week — most recently the doubled tariff on U.S. imports from India — and are being challenged by courts and other governments.
The world’s manufacturers have been particularly affected. The extended networks of diverse suppliers, and complex nature of their supply chains, have turned tariffs from a known quantity into a moving target. The shift is affecting sourcing, production and shipping. What’s more, there’s no guarantee that a management strategy implemented today will be fit for purpose tomorrow.
AI in the Supply Chain
Manufacturing margins are often razor-thin, and an unexpected jump in tariffs can easily become an existential threat. If organizations don’t have a good answer for how to absorb or mitigate the impact of a tariff increase on their supply chain, they’ll find themselves losing competitive advantage.
But for those that can set themselves up to pivot quickly — to diversify suppliers, adjust prices, and negotiate with fresh information — there’s an opportunity for differentiation.
Future-focused manufacturers are embedding AI in increasingly sophisticated ways, building on years of automation and machine learning to adapt to tariff changes effectively. The speed and granularity that AI adds to the supply chain decision-making process enables proactivity and helps organizations make the right moves when things change.
Scenario modeling is a central discipline of managing risk, especially in difficult-to-predict environments such as those roiled by tariff changes. A digital twin can act as a live model of markets and the business, using real data to simulate the effect of different tariffs on the supply chain.
AI can model various combinations of tariff restrictions, market conditions and business demands, to determine which supply routes and sources will offer the most reliability and manageable costs. It can clearly demonstrate where a new supplier, substitute ingredient or renegotiated agreement can provide incremental value and mitigate risk.
Large language models generative AI are enabling even more complex scenario planning, while simplifying the process of extracting clear answers to queries. With the ability to find potential sources of disruption or new opportunities in vast amounts of unstructured data and model their impacts, these tools can answer “what-if” questions with detailed qualitative analysis at speed and scale.
Balancing Price, Demand and Customer Sentiment
Demand and price forecasting are the most fundamental skills for supply chain decision-makers. And with tariffs heaping extra costs onto key transactions, getting the balance of price and demand right is even more delicate. Can you pass costs onto the customer, to avoid cutting into already-tight margins? Or will that make your product too expensive compared to your competitors, and damage demand?
AI enables rapid, detailed analysis of price and demand, allowing decision-makers to compare hundreds of variables to find the sweet spot for managing the impact of tariffs.
LLMs’ natural language processing capabilities enable more powerful sentiment analysis, to predict how price changes might affect the way customers view and talk about a product. Layered on top of quantitative insights, this represents a comprehensive, live view of price and demand.
AI-generated recommendations can give leaders the insights and confidence they need to make rapid-fire changes in the supply chain as situations shift. This combination of AI and human intelligence is the key to fast, data-driven decisions that deliver real strategic impact. But there are also opportunities to let AI take care of some changes by itself, to keep pace with an unpredictable manufacturing ecosystem.
For example, a business could set up parameters that trigger the system to reach out to suppliers to negotiate if a commodity hits a predetermined price ceiling. Or, if the system spots disruption in one country — from a tariff, weather event or political unrest — it can automatically switch to an approved alternative supplier in another market.
With clearly defined and validated autonomous workflows, manufacturers free up human intelligence for sophisticated, high-value decisions. They can handle partnership building and forward-facing work, backed by the real-time recommendations and analysis from AI.
With the tariff landscape changing so frequently and dramatically, reactivity can seem like the only way forward for mitigating supply chain risk and disruption. But by using AI to simulate complex tariff scenarios, forecast price and demand, and diversify networks of suppliers, manufacturers can shift to predictive and proactive supply chain management.
Mita Gupta is executive vice president and business unit head of WNS Procurement.