Thriving amid trade shifts: AI-driven strategies for retail success

Overview of opportunity 

Tariff-driven disruptions present retailers with an opportunity to rethink their operations across three key dimensions. 

1. Pricing strategies 
   Tariff pressures are intensifying the need for smarter pricing strategies—ones that safeguard margins while preserving shopper trust. In today’s environment, precision in pricing isn’t optional; it’s essential for competitiveness and profitability.  
   
   

2. Supply chain resilience 
   Disruptions expose vulnerabilities in global supply chains. Building resilience ensures business continuity and flexibility in the face of future shocks.  
   
   

3. Shopper satisfaction 
   Amid rising costs, shopper trust and perceived value are more important than ever. Consistency in the customer experience plays a vital role in maintaining loyalty- even when pricing pressures create volatility. 

Pricing strategies 

Tariff impact 

Tariffs amplify cost across categories such as groceries, apparel, electronics forcing retailers to adjust prices upwards. Retailers may even resort to ‘shrinkflation’ – reducing product sizes to mitigate price hikes diminishing perceived value. 

Strategies

Selective cost absorption  
Retailers can use Product Category Dynamics where each product category is affected differently by tariff increases, depending on shopper perception, price sensitivity, and the retailer’s strategic priorities across apparel, electronics, KVIs, luxury goods. 

How AI can help 

• AI models can segment products based on tariff exposure and simulate shopper demand to price changes. Using controlled pricing experiments, retailers can re-calibrate item-level elasticities in a structurally changed market today - enabling cost absorption strategies. 

• GenAI based alerting for competitor pricing data enables retailers to dynamically adjust their own prices in response to competitor moves. This competitive intelligence helps identifying categories where price matching is essential versus those where margin recovery is feasible. 

Cross-category margin balancing

Retailers are navigating a complex pricing landscape shaped by uneven cost inflation across categories—such as sugar-intensive beverages versus palm-oil-based soap bars. Adding to the complexity are varying shopper price sensitivities at the category and SKU level, and differing levels of pricing flexibility influenced by supplier agreements. 

How AI can help 

• Build detailed, tariff-adjusted margin profiles for each product category using scenario modeling tools such as Margin Tree Decomposition and Sensitivity Dashboards to inform where to absorb costs and where to pass them through. 

Supply chain resilience

Tariff impact 

Tariffs raise cost of materials and components, complicating sourcing decisions. They also create bottlenecks at ports and borders delaying production and inventory replenishments.  

Strategies

Supply chain optimization
AI-driven supply chain intelligence enables retailers to proactively respond to tariff disruptions by optimizing sourcing, enhancing cost transparency, and targeting high-impact negotiations. 

How AI can help

• Tariff-Aware Should-Cost modeling estimates post-tariff landed cost at SKU and BOM levels, factoring in raw material origin, manufacturing geography, and logistics combined with RAG based models that pull supplier options from countries under favorable FTAs provide new sourcing locations with trade advantages.

• AI simulators consider cost, lead time, and risk profiles of sourcing regions to support resilience-driven decisioning.

Supplier negotiations
Collaborate with suppliers to share cost burdens or explore alternative sourcing options.

How AI can help

• Flag suppliers with high revenue dependency and high SKU exposure to tariffs, prioritizing them for shared burden discussions.

• Co-pilot simulations aggregate financial health, geopolitical risk, ESG scores, and tariff trends to build dynamic supplier risk profiles.

Shopper experience

Tariff impact

Higher retail prices due to increased costs of imported goods, reduced product variety due to limiting imported items or replacing them with lower quality alternatives, delays due to supply chain disruptions erode shoppers’ trust in retailers.

Strategies

Predicting shopper behavior
Retailers don’t know how different shoppers will react to price changes, product shortages, or new offers during disruptions like tariff hikes. Traditional approaches are too slow and generic, leading to lost sales or unhappy customers.

How AI can help

• AI-powered digital twins of shopper segments simulate how different shopper types respond to pricing, availability, and assortment changes—especially those driven by tariffs. These models integrate behavioral data, psychographics, and macroeconomic signals to forecast shopper reactions with greater accuracy.

• This helps retailers tailor pricing, messaging, and engagement strategies for each segment - reducing churn risk and finding the right balance between protecting margins and maintaining shopper satisfaction during volatile times.

Discover new behavioral segments
During economic stress, like tariff hikes, shopper behaviors shift in unexpected ways. Traditional segments miss these changes, leaving retailers blind to emerging needs, preferences, or coping strategies.

How AI can help

• AI models use clustering, behavioral modeling, and generative techniques to detect new, fast-forming shopper personas - like “value-maximizers” who shift to private labels or delay purchases. These dynamic segments offer a forward-looking view of how shopper base is evolving.

• Retailers can use this intelligence to refine targeting, adjust merchandizing, and deliver relevant content that matches how shoppers are adapting under pressure - staying ahead of demand shifts and maintaining brand relevance.

Hyper-local retailing
Retailers often struggle to keep store assortments aligned with fast-changing local demand, especially during disruption from tariffs. Static planning and delayed trend recognition can lead to stockouts, overstocks, and missed sales opportunities. 

How AI can help

• AI agents continuously scan local social chatter, competitor moves, regional shopping trends and macroeconomic data to inform dynamic store-level assortment / inventory plans and even upstream buying decisions at the region × category level.

• This allows retailers to respond with relevance at the shelf, minimize lost sales, and build brand perception as responsive and locally attuned.

Conclusion

As tariffs, inflation, and evolving consumer expectations reshape the retail landscape, staying competitive demands more than reactive moves—it requires precision, agility, and foresight. AI empowers retailers to meet this moment with confidence: enabling smarter pricing, simulating shopper behavior through digital twins, and uncovering opportunities hidden within complexity.

Those who tap into these capabilities won't just weather the current challenges—they'll build a foundation for long-term advantage, trust, and growth.