Generative AI Transforms Pricing Management in the United States

Generative AI as a Key Tool for American Businesses

In the face of unpredictable tariff fluctuations, American companies are turning to generative AI to optimize their tariff management. This technology proves essential for simplifying the often lengthy and complex tariff refund process. Last year's tariff fluctuations added a new layer of complexity for importers, making generative AI indispensable for completing the time-consuming refund process. It also helps save weeks in planning complex scenarios for material sourcing.

Companies have experienced rollercoaster tariff changes over the past year, with significant tariffs applied at varying levels across different countries. While some were ultimately overturned by the Supreme Court, additional bureaucracy has emerged as companies seek potential refunds. Some are turning to AI for assistance.

EQI and KPMG: Pioneers of Generative AI

Companies like EQI, which specializes in metal components and supply chain consulting services, and customs consulting firms like KPMG, have adopted generative AI to tackle tariff chaos. Brendan Connallon, Vice President of Finance at EQI, emphasizes that this technology can quickly extract and synthesize vast amounts of data, track tariff changes, model potential supply chain scenarios, and accurately classify goods according to their government-assigned tariff codes—a highly nuanced system with over 17,000 codes.

Emil Stefanutti, CEO of Gaia Dynamics, a software company providing AI tools to help businesses automate trade compliance, stated that AI proves particularly useful in this rapidly evolving environment, as it can reduce compliance errors and save companies time. With the Supreme Court ruling, Stefanutti mentioned that importers can use AI to analyze data on where and when they paid tariffs, quantify potential overpayments, and identify areas needing corrections.

"AI can continuously track and adapt to new rules in a way that humans simply cannot do at scale," said Stefanutti.

KPMG and Tariff Refund Optimization

The consulting firm KPMG has been advising its clients on trade compliance for decades, but particularly last year, "tariffs were changing rapidly and intensely," said Andrew Siciliano, head of global and U.S. trade and customs practices at KPMG. Business leaders needed real-time data quickly to make decisions, which is why KPMG launched an AI-powered tariff modeling tool. The firm's clients include many large companies importing goods ranging from automotive parts to consumer products and pharmaceuticals, using multiple entry ports and customs brokers. KPMG takes its clients' decentralized customs declarations and product information from their suppliers and freight forwarders—the intermediaries between importers and their transport suppliers—and integrates this data into the tariff modeling tool, Siciliano explained.

This approach has helped KPMG's clients navigate the refund application process for excessive tariff payments resulting from policy changes that took effect after the Supreme Court overturned certain tariffs. Many trade rules have nuanced exceptions, leading some companies to pay multiple tariffs when they should have only paid one. Siciliano stated that his company uses AI to interact with a client's data and better understand which products come from which factories, thereby reducing the number of products eligible for refunds.

Although the refund system is still under development, there may still be confusion and uncertainty, Connallon stated. He told Business Insider that he expects the process to be "an administrative nightmare." Before AI, manually sorting through thousands of data points from customs declarations to spot overpayments could take weeks or months—or might not happen at all due to complexity, Siciliano noted. Now, an importer can query the AI, which immediately provides the information.

AI and Complex Scenario Modeling

AI also allows for weeks of savings in scenario planning. An importer might wonder how costs could change if they shifted their sourcing from China to Vietnam, for example. Instead of taking weeks to update multiple spreadsheets, AI can model scenarios in just a few clicks, Siciliano said.

Connallon indicated that EQI uses AI similarly to model potential sourcing scenarios. The company utilizes the Altana AI platform, which focuses on supply chain management and trade compliance.

In a potential shift of sourcing from country A to country B, EQI uses AI to model total costs, taking into account tariffs, manufacturing costs, and shipping rates. For manufacturing, which sources thousands of different products from many locations, "the complexity becomes extremely dense very quickly," Connallon stated. "So, AI helps us simplify that." EQI sends the simplified data to its trade attorneys, who can interpret it in a few hours, Connallon specified.

"We have transformed something that would take weeks into a same-day feasible process," he said.

He added that "AI is not good at critical thinking," and that humans are essential for sourcing decisions. For instance, the AI model might indicate that sourcing all materials from a single country yields the greatest savings, but business leaders must consider the bigger picture, Connallon stated. Supply chain leaders have learned, especially in recent years, that sourcing solely from one country carries risks, such as product shortages or delays if a geopolitical or economic issue disrupts trade flows.