Beyond the Tariff Hike: Reclaiming Retail Profitability With AI-Driven Pricing and Assortment Optimization
Retailers today are battling a relentless gauntlet of unpredictability: geopolitical instability, supply chain shocks, and persistent inflation. For leaders, the mission is singular: to protect the bottom line in a market where external costs, particularly tariffs, can erode margins overnight.
Traditional pricing models, reliant on static data and historical markups, simply cannot keep pace with this velocity of change. This growing gap between market speed and operational agility has made one thing clear: margin recovery isn't guesswork; it's a structured, measurable process powered by artificial intelligence and data engineering.
The era of historical markups is over. In today's volatile market, margin protection requires moving beyond reactive spreadsheets to proactive, predictive intelligence. AI is the non-negotiable engine that transforms complex external shocks like sudden tariffs into manageable, micro-level pricing and assortment adjustments, ensuring retailers don't sacrifice customer trust while safeguarding profitability.
The 3 Pillars of AI-Driven Margin Resilience
In our experience, there are three critical areas where AI transforms cost absorption into competitive advantage:
1. Predictive and Dynamic Pricing Optimization
Tariffs and supply chain disruptions represent abrupt cost increases that cannot be addressed with blanket, reactive price adjustments. The risk is twofold: set the price too high and you lose customer loyalty; set the price too low and you hemorrhage profits.
AI-driven systems solve this by analyzing a multitude of variables in real time, including competitor price moves, local demographics, and crucial price elasticity models. This capability allows retailers to differentiate between key value items (KVIs) and insensitive items.
By running dynamic scenarios, AI allows retailers to anticipate tariff impacts and adjust pricing with precision, ensuring costs are recovered without unnecessarily reducing demand.
2. Automated Tariff and Supply Chain Compliance
The complexity of global trade rules, especially tariff classification, is a major source of financial risk. Manually classifying thousands of SKUs is tedious and error prone, resulting in penalties.
To combat this, AI and machine learning can instantly analyze product attributes, assign correct tariff classifications, and provide real-time smart notifications when trade policies change.
Additionally, advanced data engineering platforms are required to integrate external data, such as geopolitical shifts, trade agreements, and commodity cost indices, directly into the planning engine. This creates an intelligent supply chain control tower that shifts from a reactive system to one focused on autonomous interventions. If a tariff is imposed on a key raw material from Supplier A, the system can autonomously identify and model cost-effective alternatives from Supplier B, minimizing financial impact and ensuring production continuity.
3. Strategic Assortment and Promotion Optimization
As costs rise, retailers must reassess their product mix to focus resources on high-performing SKUs. AI-powered assortment planning identifies top-selling, high-margin items and flags underperformers. By reducing assortment width and prioritizing high-demand items, retailers avoid overcommitting to costly inventory that may require deep markdowns in the future.
Furthermore, AI models optimize promotional activity, identifying where and when a discount will maximize volume without undue margin erosion, instead of broad discounts that unnecessarily cut into profit.
The Path to AI-Powered Outcomes
For C-suite and technology leaders, the adoption of data and AI is no longer an option; it's a mandatory move to build resilience. It's about evolving the organizational mindset from simply managing costs to engineering profit. By integrating AI-driven insights with human judgment, retailers can transform external unpredictability into a measurable advantage.
Vrinda Khurjekar is vice president, solutions consulting, AMER, Searce, a modern technology consulting firm that empowers clients to futurify their businesses, leveraging cloud, AI and analytics.
Related story: Modernizing Retail Supply Chain Challenges With AI
Vrinda Khurjekar is vice president, solutions consulting, AMER, Searce. A techie turned business leader, Vrinda is passionate about driving technology-led transformation and helping businesses futurify by leveraging the latest technologies. Vrinda has been in various roles over the last 15 years at Searce, a core member of the Searce global exec team. Vrinda has personally participated in leading many large clients through their digital transformation journeys. Vrinda believes in the power of customer empathy, listening to clients and partners, and being a trusted partner to anyone she works with.





