How AI reshaped holiday shopping: What it means for consumer goods businesses

Artificial intelligence reshaped the 2025 holiday shopping season at a scale not seen before, redefining how consumers discover products, make purchase decisions and seek customer support. With AI-driven traffic surging nearly 700% year over year and peak season customer service tasks handled increasingly by automated agents, the consumer goods sector entered 2026 with a new digital performance baseline.

For leaders planning the next six to 12 months, the most recent holiday season offered a practical blueprint for where to invest first, and where AI will become table stakes by year-end 2026. Companies that operationalize AI across discovery, service, and fit or virtual try‑on will be better positioned to strengthen margins, reduce friction and build deeper customer loyalty in the year ahead.

The need for resilience amid ongoing trade volatility

While AI was the defining commercial force of the holiday season, it unfolded against a backdrop of elevated cost and trade uncertainty. In February 2026, the U.S. Supreme Court struck down a significant portion of recently imposed global tariffs, ruling that the Trump administration exceeded statutory authority under the International Emergency Economic Powers Act (IEEPA). The decision provided near‑term relief for many consumer goods importers whose margins had been pressured throughout 2025.

However, the 2025 holiday season made clear that volatility, not stability, remains the operating reality. Alternative tariff mechanisms under sections 122 and 301 of the Trade Act of 1974 and section 232 of the Trade Expansion Act of 1962 remain available, maintaining uncertainty around sourcing costs, pricing and inventory strategy.

In addition, geopolitical disruptions raise the premium on planning speed. The current conflict in the Middle East is already adding uncertainty and disruption to global supply chains through energy, shipping and insurance channels, and companies are responding by stress-testing lead times, landed costs and availability under multiple scenarios. For consumer goods brands, pragmatism is key for the rest of 2026. Plan for higher volatility in transportation and input costs, and prioritize faster reforecasting and inventory rebalancing cycles. These needs strengthen the case for AI-enabled demand sensing and scenario modeling.

The brands that performed best during the holiday period were able to model cost changes quickly, test pricing elasticity and rebalance inventory dynamically—capabilities increasingly enabled by AI‑driven forecasting and planning tools. For the rest of 2026, the planning advantage will come from speed. Brands that can reforecast demand, reprice selectively and rebalance inventory in weeks (not months) will defend margin without over-discounting.

AI as an economic engine

The 2025 holiday period did more than deliver record online sales. It revealed how deeply AI is now embedded in the commercial engine of consumer brands—marking a turning point in digital commerce performance. Online spending reached $257.8 billion for the season (a 6.8% increase year over year), demonstrating resilient consumer demand despite ongoing economic and cost pressures. At the same time, AI-referred traffic increased roughly 693% year over year, emerging as one of the strongest conversion sources across retail sites.

This surge was fueled by rapid improvements in generative search, conversational shopping interfaces, automated recommendations and AI‑powered merchandising. The result was not simply more traffic, but better traffic: Consumers arrived with clearer intent, higher confidence and a greater willingness to convert.

For consumer goods categories such as apparel, beauty, home decor and personal care—where trust, visualization and differentiation are critical—AI became central to value creation during the most important selling window of the year. In 2026, brands should assume this level of AI-driven demand shaping will persist, and should leverage it for marketing, merchandising and measurement to capture peak periods and more.

The 2025 holiday season demonstrated that AI-driven discovery is no longer experimental—it is foundational. Compared with traditional search and social channels, AI-powered discovery delivered meaningfully higher conversion rates by providing shoppers with more relevant, contextual and personalized product experiences.

Elevating customer growth and service through intelligent discovery and agentic support

For consumer goods brands, AI-enabled discovery translated into:

• Smarter predictive recommendations based on style, routine, compatibility and past behaviors
• Dynamic product detail page experiences, including adaptive copy, imagery and content sequencing
• Personalized bundles and cross-category suggestions that increased relevance
• Higher average order value, as customers found the right products faster and with greater confidence

As AI becomes embedded across search engines, marketplaces and owned brand experiences, early adopters of AI-powered merchandising will have a structural advantage in share capture and efficiency going forward.

Beyond discovery, AI delivered measurable operational leverage during the holiday surge. Brands experienced a 142% increase in customer tasks handled by AI agents, spanning order status updates, delivery tracking, gift inquiries and returns initiation. These agentic workflows produced two critical outcomes during peak periods:

• Reduced strain on human support teams, preserving service quality despite volume spikes
• Faster response times, improving customer confidence and reducing friction at checkout

Looking ahead, the winners will be the brands that operationalize AI features rather than just deploying them. In practice, that means tying AI-driven discovery and service to measurable key performance indicators (conversion, average order value, deflection and repeat rate) and making data-driven adjustments more often, such as weekly.

For middle market consumer goods companies, where service capacity is often constrained, the 2025 holiday season proved that agentic AI can deliver enterprise-grade customer experiences without enterprise-scale staffing. Importantly, these systems also generate structured, auditable data that could be leveraged to improve logistics planning, customer communications and inventory decisions well beyond the holiday window. This matters most in the nonpeak months. AI agents can convert service from a cost center into a retention lever by proactively resolving issues before they become returns or chargebacks.

AI-powered sizing, fit and virtual try-on: From differentiator to expectation

One of the clearest behavioral signals from the 2025 holiday season was consumers’ growing expectation for tools that reduce purchase uncertainty. AI‑enhanced sizing recommendations, shade matching and virtual try‑on (VTO) experiences became more accurate and more widely adopted across apparel, footwear, beauty and skin care.

These capabilities directly influence:

• Conversion rates, by increasing shopper confidence
• Customer satisfaction, by better aligning expectations with results
• Return rates, by helping customers select the right product the first time

In the months to come, as these tools become normalized, brands that delay adoption risk structurally higher return costs and weaker repeat purchase behavior. By late 2026, fit and try-on experiences will increasingly influence conversion the way reviews did a decade ago. Brands should pilot one high-impact use case now (fit, shade or VTO) and scale it ahead of the next peak season.

AI becomes a hedge against cost and margin volatility

The lessons of the 2025 holiday season extend beyond revenue growth. As trade policy, transportation costs and consumer demand continue to shift unpredictably, AI is emerging as a strategic hedge. Consumer goods companies are using AI to:

• Improve demand forecasting accuracy.
• Model pricing elasticity in near real time.
• Optimize inventory placement and replenishment.
• Support supplier diversification and sourcing decisions.

In 2026, the goal is not to develop perfect forecasts, but to recognize scenario cycles and early signals (cost, lead times, and demand shifts) that let teams act before margin erosion shows up in financial results.

Rather than relying on blunt price increases, AI‑enabled planning allows brands to protect margins while maintaining customer trust. This advantage became increasingly visible during the high‑stakes holiday period.

Middle market implications

Middle market consumer goods companies have a unique opportunity. AI adoption no longer requires custom builds or large engineering teams. Instead, companies can:

• Deploy modular AI tools that integrate with existing commerce platforms.
• Pilot focused use cases with clear KPIs, such as service automation and fit recommendations.
• Build a lean, scalable data foundation.
• Tie AI initiatives directly to improved margin, reduced returns and lifetime value.

Success requires disciplined execution, clear governance, strong data quality and well‑defined guardrails around content, accuracy and model use. A practical 60-to-90-day path is to pick one revenue lever (e.g., AI-driven discovery) and one cost lever (e.g., agentic service), define three to four KPIs, run a pilot, then scale the approaches that improve the metrics. This keeps AI from becoming a “tool rollout” and forces it to become a performance program.

The takeaway

The 2025 holiday season marked a permanent shift in how consumer goods brands compete. AI is no longer a layer on top of commerce; it is embedded in discovery, service and decision making.

In the months to come, consumer goods companies should embed AI across product discovery and customer service, offering sizing and fit experiences such as virtual try‑on. When paired with focused pilots, measurable KPIs, and strong data and content governance, these tools can drive sustainable margin improvement, operational efficiency, and stronger customer trust and loyalty. By the time the 2026 holiday season arrives, these capabilities will increasingly separate share gainers from share forfeiters, and the window to build them is now.