Retailers are bracing for another wave of supply chain disruption as new tariffs threaten to drive up costs across industries. With global trade policies shifting, companies are scrambling to assess the impact on their operations, margins, and ultimately, consumers' wallets. The question now isn’t just how much prices will rise—but how businesses can adapt.
Technology is playing a crucial role in this transformation. As Peter Tardelli, Senior Sales Strategy Expert at Palantir, recently highlighted, advanced supply chain solutions enable retailers to rapidly integrate enterprise-wide data, assess country- and tariff-based risks, and automate critical sourcing decisions. By leveraging tools that map product cost journeys across enterprise resource planning (ERP) systems, warehouses, human resources, and delivery networks, companies can pinpoint high-risk stock-keeping units (SKUs) and proactively adjust their strategies to maintain profitability.
But even with these tools, the challenges are steep. Businesses must decide whether to absorb higher costs, pass them on to consumers, or find alternative solutions. Retailers are adjusting sourcing strategies to mitigate risks by exploring partnerships in low-tariff regions and nearshoring operations. Predictive modeling has proven invaluable in this process—retailers are using AI-generated scenarios to preemptively secure inventory and optimize pricing strategies.
Real-time simulation of multiple tariff scenarios is now a competitive necessity. AI-powered analytics can rapidly analyze country-specific duties, evaluate alternative vendors, and automate pricing adjustments to keep businesses agile. For retailers, this enables cost savings, supplier diversification, and sustained price competitiveness amid geopolitical changes.
“When tariffs are imposed or adjusted, online retailers must quickly assess which SKUs are most at risk and strategize to manage cost fluctuations without impacting customer experience. Brands need to identify affected products based on country of origin and historical sales data. High-risk products—those with high return rates, low resale value, or complex reverse logistics—require careful evaluation to minimize financial exposure. Once identified, brands can explore alternative sourcing strategies or adjust return policies to mitigate rising costs. However, clear and transparent communication is essential to maintaining consumer trust,” says Kristen Kelly, SVP of Product at Loop Returns.
Predictive modeling and AI-powered scenario planning are also helping businesses optimize supply chain efficiency. By identifying the most cost-effective shipping routes, balancing inventory, and selecting the most affordable labels, companies can minimize logistics expenses and ensure product availability despite tariff challenges.
“In addition, reverse logistics companies use historical returns data and forecasting models to anticipate which orders might result in returns,” Kelly adds. “This helps e-commerce merchants make better merchandising and inventory decisions while also improving the shopping experience to reduce returns in the first place. Predictive analytics can even estimate the resale value of returned products, ensuring businesses can recover as much value as possible and avoid unnecessary losses.”
From a policy standpoint, future tariffs will likely reflect ongoing geopolitical tensions and trade realignments. Retailers should prepare for volatility by building flexible supplier networks and leveraging trade incentives where available. Policymakers can reduce uncertainty by negotiating stable trade agreements and providing transparent tariff guidelines. Collaboration between governments and businesses is key to strengthening supply chain resilience—joint investment in infrastructure, trade facilitation, and real-time data sharing will help businesses navigate these disruptions more effectively.
“Retailers must take a proactive approach,” says Carla Niña Pornelos, General Manager of Wardnasse. “By leveraging AI, predictive analytics, and strong supplier relationships, companies can mitigate risk, optimize costs, and maintain a competitive edge in a rapidly changing trade environment.”
International shipping is gradually stabilizing, but delays often stem from inefficiencies within e-commerce retailers' systems. A lack of accurate inventory management can prevent products from being available at the right place and time. Poor data quality leads to bottlenecks in order fulfillment, making it essential for retailers to have real-time visibility into stock levels—whether fulfilling orders from a warehouse or a physical store.
Errors in that data cause delays, because precious delivery time is now spent trying to locate the stock. Retailers can address this through digital enablement – by getting their systems to talk to each other and improving business intelligence.
"E-commerce retailers should always be asking: “What orders am I going to receive and how am I going to fulfill them?” Data-driven systems are part of the solution. Demand signaling, or predictive analytics, refers to AI that predicts future inventory demand. Sophisticated insight into what demand is coming helps retailers have the products ready to dispatch when the orders come in,” says Travis Erridge, co-founder and CEO of TMX Transform.
As trade policies continue to evolve, retailers must remain agile in navigating supply chain challenges. By leveraging AI-driven analytics, predictive modeling, and strategic supplier diversification, businesses can mitigate risks and adapt to tariff fluctuations. Collaboration between policymakers and industry leaders will be key to fostering a resilient trade environment, ensuring retailers can maintain profitability and competitiveness in an unpredictable global market.
This article was originally published by Dennis Mitzner at Forbes on March 25 2025.