In the wake of renewed tariff pressures, fashion brands are grappling with the financial and operational ramifications of international trade disputes. Is AI the answer to a workaround?
Following his campaign trail pledge to address trade imbalances, President Donald Trump enacted additional tariffs on Chinese-made goods, introducing a 10 per cent tariff on imports to the United States, effective from 4 February. (Twenty-five per cent duties on Mexico and Canada were announced simultaneously but suspended before taking effect.) Given China’s central role as a manufacturing hub for the fashion industry, this has placed significant strain on brands, particularly those reliant on the country’s extensive supply chain for raw materials, textiles, and finished goods.
Brands across various segments — ranging from fast-fashion giants like Shein to premium labels that produce select lines in China — are grappling with rising costs, supply chain disruptions, and increased tariffs. These challenges are especially acute for mid-tier and direct-to-consumer brands that operate on razor-thin margins, as they have less pricing power to absorb higher expenses.
Amidst the uncertainty, a rising tide of AI-driven solutions is emerging as an indispensable tool to help fashion companies mitigate these disruptions. “In the past, brands reacted to tariff hikes after the damage was done — scrambling to cut costs or absorb losses once duties were applied,” says Arun Rai, director and co-founder of the Robinson College of Business Center for Digital Innovation at Georgia State University. “AI flips that script, giving companies the tools to simulate, adjust, and optimise before tariffs cut into margins.”
A rule that allowed goods under a certain value to be imported duty free from China into the US is in jeopardy, with industry-wide implications.
Advancements like AI-based “digital sandboxes” help brands to model the financial impact of shifting duties, trade agreements or alternative suppliers, he explains, allowing them to navigate these changes with greater foresight. Proponents say AI can adjust forecasts, optimise stock strategies, fine-tune fulfilment, find new suppliers and enhance freight and logistics playbooks in response to sudden tariff changes. Will it work?
Reading the ripple effects
Predictive analytics are now a necessity for anticipating tariff-induced cost fluctuations. “Tariffs can reshape entire cost structures overnight, so the real challenge for brands isn’t just adjusting to price hikes but understanding the ripple effects,” says Adil Bouhdadi, co-founder and CEO of Autone, an AI-powered demand forecasting and inventory optimisation platform. The predictive capabilities of AI allow brands to prepare in advance for disruptions caused by tariffs.
Ahead of the US presidential inauguration, platforms such as Prediko — inventory planning software designed for Shopify brands — observed a surge in orders relative to forecasted sales, indicating that businesses were preemptively stockpiling in anticipation of potential tariff hikes. This aligns with broader trends: companies were strengthening their fulfilment networks, particularly in the US, in preparation for shifting manufacturing away from China.
As brands reassess their manufacturing locations, AI tools enable more accurate forecasting of lead times, helping prevent both overproduction and stockouts. Rodney Manzo, founder and CEO of Anvyl, a supply chain visibility platform, emphasises that “predicting lead times is going to become more important than ever” as businesses navigate the complexities of evolving trade dynamics. With AI, brands gain access to actionable data, ensuring they remain agile in the face of tariff changes.
Strategies for stock and sales
The traditional approach to inventory management — stockpiling months of goods and hoping demand aligns — has become increasingly untenable for many brands. Bouhdadi says that AI systems not only help brands mitigate losses when tariffs strike, but they can also optimise margins and timing to ensure products are sold in the most efficient markets. AI can even suggest small adjustments to product materials that bypass tariff hikes without compromising on consumer satisfaction, he says.
AI-driven inventory strategies allow for more precise allocation of goods to lower-tariff regions. “AI lets businesses stockpile inventory in locations where tariffs are lower and optimise sourcing to reduce exposure to high-cost markets,” says Benjamin Kelly, CEO of Singuli, an AI-powered inventory optimisation platform. For brands with complex international supply chains, this proactive approach to inventory placement provides a crucial competitive edge.
However, the shift towards multi-country sourcing and diversified supply chains is far from simple, requiring extensive restructuring of established systems. Brands must navigate challenges such as managing new supplier relationships, ensuring consistent product quality across different regions, and aligning operations with fluctuating costs and trade regulations. Additionally, diversifying supply chains involves considerable investment in logistics, technology, and skilled personnel to monitor and optimise processes effectively. “This isn’t something that can be set up overnight,” Kelly cautions.
Brands must carefully assess the potential opportunity costs of pulling forward inventory — a decision that AI tools can help mitigate. This approach can be costly for brands, tying up capital that could be better invested elsewhere. It also raises storage costs and increases the risk of overstocking, especially in a fast-paced, trend-driven fashion market. Premature inventory may lead to unsold goods, limiting flexibility to adapt to shifting consumer demands or unforeseen market disruptions.
Fashion brands are laser-focused on sales, pulling every possible lever to protect their margins. “Maximising full-price sell-through is especially tricky for retailers juggling countless SKU variations across size, colour, and fit,” says Benjamin Fels, CEO and co-founder of Pendulum, which positions itself as the OpenAI of supply chain operations.
Advanced AI models now integrate real-time signals — everything from influencer-driven demand spikes and local search trends to granular weather forecasts — alongside historical sales data. The result is smarter, site- and channel-specific allocation strategies that minimise markdowns and optimise inventory. AI-powered platforms that tackle procurement, inventory, pricing, and promotions ensure the right product is in the right place at the right time, says Fels.
Fighting freight costs
With tariffs disrupting supply chains, freight and logistics have become critical battlegrounds. AI can be used to optimise shipping routes and consolidate freight to reduce expenses.
Flexport, a B2B freight technology platform, uses AI to ensure that brands can adjust their shipping strategies in real time, responding to new tariffs and regulations. “AI allows us to parse and interpret rules at scale, ensuring businesses stay ahead of compliance shifts,” says Alex Nederlof, director of engineering at Flexport.
Navigating customs compliance is a high-stakes game for fashion brands moving products across borders. One misfiled product code or missing document can trigger unexpected tariffs, delays, or even seized shipments. AI is rewriting the rulebook, automating key processes to keep goods moving and costs in check, says Nederlof.
In the scramble to comply with a slew of regulations and standards, brands are using different systems that demand different data, putting pressure on suppliers. Attempts to simplify the system are underway.
One of the biggest friction points is document accuracy. AI-powered systems scan invoices, customs declarations, and shipping documents, extracting critical details — product descriptions, harmonised system (HS) codes, country of origin — and cross-checking them for errors. The payoff is fewer costly misclassifications and reduced risk of overpaying tariffs or fines.
Correct classification is another advantage. By analysing product descriptions, historical data and even images, AI can validate HS codes and flag potential disputes before they become expensive problems. Brands often don’t realise they’re misclassifying items until they’re hit with unexpected duties or penalties, says Nederlof, and AI helps eliminate that risk upfront.
Tariff-specific tools
The future of AI in fashion trade goes beyond merely responding to tariffs — it is about fundamentally reshaping global trade strategies. Amy Morgan, VP of trade compliance at Altana, an AI-based company that maps and analyses global supply chains, explains how tools like the company’s Tariff Scenario Planner are enabling brands to model the impacts of tariffs on individual products. “By simulating ‘what-if’ scenarios, companies can quickly identify alternative sourcing opportunities and adapt their strategies accordingly.”
Pull Logic is also developing a Tariff Evaluator Agent with assistance from select manufacturing partners, designed to help brands simulate tariff impacts, test pricing strategies and uncover cost-saving opportunities, says co-founder and COO Taresh Grover. The tool models tactics like dynamic or tiered pricing to offset tariff-driven cost increases — helping brands protect margins without alienating customers. Once live, it will offer apparel brands a data-driven approach to navigating trade volatility.
As AI continues to evolve, it will also support regulators by identifying non-compliance risks, improving policy enforcement, and creating more dynamic trade strategies. “AI will help businesses and regulators navigate the complexities of global trade with greater agility and informed confidence,” Morgan adds.
Ultimately, AI is a powerful ally in navigating today’s complex supply chain landscape, but its true value lies in how brands leverage it. Clean, accurate data is the foundation for optimising AI’s potential, yet it’s the blend of AI insights and strategic, human decision-making that will drive meaningful results, says Paul Magel, president of the supply chain technology division at retail software provider CGS. For brands looking to thrive in this dynamic environment, the key lies in using AI to complement, not replace, a well-rounded approach to supply chain management.
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