Table of Contents

1. Key Highlights
2. Introduction
3. How Mastercard Reached the 5.5% Forecast
4. Online vs. In-Store: A Complementary Relationship
5. Defining “AI Power Users” and Why They Matter
6. Practical Ways AI Is Already Shaping Holiday Purchases
7. Agentic Commerce: Automation That Buys on Your Behalf
8. Jewelry, Handbags and Cosmetics: Categories Built for Last-Minute Spikes
9. The Price Effect: Half the Growth Is Inflation-Driven
10. Who Benefits from AI-Driven Shopping?
11. What Retailers Should Do Now
12. Consumer Considerations: Privacy, Control and Subscription Dynamics
13. Small Business and Boutique Strategies to Capture AI-Driven Demand
14. Fraud, Chargebacks and Trust in an AI-Driven Marketplace
15. Examples of AI-Assisted Holiday Use Cases
16. Competitive Risks and Market Dislocations
17. Measuring Success: KPIs for an AI-Influenced Holiday
18. Regulatory and Ethical Considerations
19. What This Means for Holiday 2026: Practical Takeaways
20. FAQ

Key Highlights

• Mastercard Economics Institute forecasts a 5.5% year-over-year increase in U.S. retail sales (excluding autos and gasoline) from Nov. 1 through Christmas Eve 2026, with online sales projected to rise 11% and in-store sales 3.6%.
• Consumers using paid AI services — labeled “AI power users” — spend differently: they shop earlier, diversify merchants (including boutiques), and concentrate purchases across travel, apparel and jewelry; agentic commerce could put AI-driven buying on autopilot for hundreds of millions by 2030.
• Roughly half of the projected spending gain reflects higher prices rather than increased volume, while late-week and last-minute buying remains significant in categories like jewelry, handbags and cosmetics.

Introduction

Mastercard’s latest forecast anticipates one of the most robust holiday shopping seasons since 2022, propelled by healthy household finances and a notable shift in how people discover, compare and buy products. Online demand is expected to outpace in-store growth, yet brick-and-mortar locations remain integral to purchase journeys. The distinctive element in this cycle is widespread AI adoption among shoppers: those who pay for AI services show different timing, merchant choice and purchase patterns, suggesting technology is no longer merely advisory but is starting to reshape marketplace dynamics. For retailers, marketers and consumers alike, the coming season will test which strategies translate AI-driven interest into sustained sales and which fall short when prices and timelines compress.

How Mastercard Reached the 5.5% Forecast

Mastercard’s Economics Institute (MEI) combined transaction data with macroeconomic indicators to project holiday retail performance from Nov. 1 through Christmas Eve. The forecast excludes autos and gasoline to isolate core retail behavior. Key inputs included employment levels, wage growth and household wealth trends; MEI concluded consumers enter the season with meaningful purchasing power. At the same time, MEI adjusted for inflationary pressures, noting that roughly half of the projected increase in dollar spending stems from higher prices rather than a commensurate increase in item volumes.

A careful reading of the numbers shows two dynamics operating simultaneously. First, demand remains solid: consumers are shopping and engaging with a broad range of categories. Second, elevated prices are amplifying nominal spending figures. That combination explains why the headline growth feels robust while individual retail managers may still encounter customers sensitive to price and value.

Online vs. In-Store: A Complementary Relationship

MEI’s projection that online sales will grow 11% while in-store sales rise 3.6% tracks a longer trend toward omnichannel consumer behavior. Shoppers increasingly discover products digitally, examine reviews and comparison-shop online, then make purchases either via e-commerce or in physical stores. The physical store functions now as both a showroom and a conversion point.

Consider the gift-buying workflow of a typical holiday shopper. They might spot a trending handbag on social media, use a paid AI tool to identify similar styles and lowest available prices across sellers, then visit a nearby boutique to inspect materials and confirm fit before buying on the boutique’s site. That blend of remote discovery and local verification drives both online traffic and in-store footfall. For retailers, that creates opportunities and friction: a well-integrated inventory and pricing strategy can capture demand wherever the shopper chooses to finalize the purchase; disjointed systems will lose it.

Retailers that succeed will be those that treat online and in-store channels as parts of a single customer journey. Real-time inventory visibility, consistent pricing across channels, and flexible fulfillment (ship-from-store, buy-online-pickup-in-store) are no longer differentiators — they are prerequisites.

Defining “AI Power Users” and Why They Matter

MEI’s analysis compared spending patterns between consumers who subscribe to paid AI services and those who do not. These "AI power users" include subscribers to advanced conversational assistants, productivity tools with integrated shopping capabilities, and emerging agentic services that take autonomous actions on the user’s behalf.

Paid AI subscriptions serve as a behavioral proxy. They signal users who invest time and money into AI tools and, by extension, who are more likely to use technology to optimize purchase decisions. Mastercard’s data points to several consistent traits among these shoppers:

• Earlier holiday spending: AI power users allocated a larger share of their holiday budgets before Thanksgiving in 2025.
• Broader merchant mix: they frequent a wider array of stores, including smaller independent retailers and boutiques.
• Category concentration: travel, clothing and jewelry commanded larger portions of their holiday expenditures.

Those patterns matter because they illustrate how technology shifts not just when people buy, but where they buy. If AI helps consumers discover niche sellers or compares small-batch jewelry makers against national brands, the floor plans of competitive advantage change. Large retailers cannot assume scale will automatically win out; relevance, curation and trust increasingly matter.

Practical Ways AI Is Already Shaping Holiday Purchases

AI influences holiday shopping across three broad stages: discovery, comparison and transaction. Each stage presents concrete examples that illuminate how AI power users behave.

Discovery

• Personalized recommendations: AI models analyze browsing, past purchases and even social signals to surface gifts a shopper might not have considered.
• Trend spotting: real-time trend detection steers consumers toward products gaining momentum, which is especially valuable for categories like handbags and apparel.

Comparison

• Price and feature aggregation: paid AI tools can compare prices across marketplaces, flag deals and present trade-offs (e.g., diamond clarity vs. carat for engagement rings).
• Rapid filtering: advanced prompts let shoppers specify constraints—budget, delivery date, ethical sourcing—so the AI narrows options quickly.

Transaction and Agentic Commerce

• Streamlined checkout: integrations with digital wallets, saved payment credentials and instant fulfillment options reduce friction.
• Agentic actions: the next stage pairs discovery and transaction. An agent could be instructed to “buy the best engagement ring under $7,500 with a GIA certificate and delivery by Dec. 20,” then search, verify seller ratings, and complete the purchase with minimal user intervention.

Illustrative scenario: Engagement ring shopper Imagine a buyer named Maya. She wants a solitaire engagement ring, $6,000 budget, conflict-free stones, and delivery within two weeks. Maya uses a paid AI assistant configured with her preferences. The assistant scans mainstream retailers, independent jewelers and verified secondary markets, filters for certifications and return policies, compares insurance and setting options, and presents the top three picks ranked by value and seller reliability. Maya chooses one; the agent negotiates a small discount via a chat interface, applies a stored payment method, and schedules in-store pickup for a partner jeweler. A process that would have taken days of research becomes a single, mixed-initiative interaction.

That degree of efficiency explains why AI power users both shop earlier and across more merchants: AI reduces search costs and increases the perceived rewards of looking beyond the obvious.

Agentic Commerce: Automation That Buys on Your Behalf

Mastercard highlighted agentic commerce as an emerging frontier. The firm estimates that more than 300 million online shoppers globally could routinely use AI agents to shop and pay by 2030. Agentic commerce differs from present-day recommendations because agents can:

• Execute multi-step transactions (search, verify, purchase).
• Negotiate terms (discounts, delivery dates).
• Manage post-purchase activities (returns, warranty registrations).

The shift from recommendation to execution changes the seller-buyer dynamic. Rather than competing for attention, vendors will compete to be part of agent-accessible ecosystems. That raises questions about discoverability and standardization. Agents will prefer sellers with clear metadata: consistent SKU descriptions, standardized return policies, reliable fulfillment SLAs, and strong reputations reflected in verifiable reviews.

Retailers unable to surface in agentic queries risk becoming invisible to the most efficient shoppers. Conversely, merchants that enable agent-friendly APIs, structured data and transparent terms will enjoy amplified exposure.

Jewelry, Handbags and Cosmetics: Categories Built for Last-Minute Spikes

Mastercard’s analysis of the 2025 holiday season showed concentrated late-week spending in specific categories. Over 35% of in-store spending between Nov. 22 and Christmas Day in jewelry, handbags, department stores and cosmetics occurred during the final week before Christmas. Moreover, average purchase values in those categories rose steadily from Dec. 15 and peaked on Christmas Eve.

Why do these categories spike late?

• Gift urgency: jewelry and handbags carry emotional and social signals appropriate for last-minute, high-impact gifting.
• Visibility and verification: shoppers often prefer to see high-value items in person before purchase, pushing some transactions to the final week.
• Packaging and services: gift wrapping, personalized engraving and in-store consultations often occur closer to gifting dates.

Retail implications:

• Staffing and inventory: retailers should prepare for surges in high-margin categories with contingency staff and inventory buffers during the final week.
• Fulfillment promises: accurate real-time inventory and expedited fulfillment options (same-day delivery, in-store pickup) convert last-minute intent into sales.
• Upsell opportunities: customers shopping late for a jewelry purchase are more receptive to add-on services—insurance, expedited cleaning, or premium packaging.

Physical storefronts remain essential for these categories even as online research dominates discovery. A shopper may identify a necklace online, but the tactile confirmation and immediate gratification of an in-store purchase on Dec. 23 still drives the transaction.

The Price Effect: Half the Growth Is Inflation-Driven

Mastercard reported that roughly half of the projected spending increase reflects higher prices. That observation distinguishes nominal spending growth (dollars spent) from real volume growth (units purchased or services consumed). Several implications follow:

• Gross merchandise value (GMV) can rise while consumer unit demand remains flat or grows modestly.
• Retailers should parse their internal KPIs: revenue increases driven by price inflation require different strategic responses than those driven by volume increases.
• Promotional strategies matter more when consumers are price-sensitive. Discounts, bundling, loyalty perks and targeted rebates preserve perceived value.

Consider two retailers with identical sales growth in dollars but different unit trends. The retailer selling more units benefits from real market share gains; the other may be maintaining share only because of price increases. The latter faces potential demand elasticity risks if prices fall or competitors offer more attractive alternatives.

Who Benefits from AI-Driven Shopping?

AI power users are not a monolith, but Mastercard’s data suggests they often have higher incomes, greater willingness to pay for convenience and a proclivity for subscription services. That creates a tailwind for several types of sellers:

• Independent and boutique merchants: AI-driven discovery can surface niche sellers that would otherwise lack scale, enabling them to reach consumers more efficiently.
• Curated platforms: marketplaces that emphasize quality curation and reliable fulfillment become trusted sources for agents to execute purchases.
• Experience-focused retailers: stores that offer exceptional in-person experiences (personalized fittings, exclusive packaging, expert consultations) capture value that agents may not fully substitute.

Small businesses can leverage AI in two ways. First, by ensuring their product data is structured and accessible, they increase the odds of being recommended by AI tools. Second, they can adopt AI-assisted customer service and marketing tools to personalize outreach and streamline operations.

What Retailers Should Do Now

The holiday period is compressed and competitive. Retailers should adopt a dual posture: optimize for immediate seasonal demand while investing in systems that will make them agent-accessible over the next three to five years.

Short-term actions

• Tighten inventory accuracy: invest in synchronized inventory across channels to prevent lost sales and abusive cancellations.
• Promote clear shipping cutoffs: communicate delivery promises prominently and offer guaranteed last-minute fulfillment options.
• Staff strategically: allocate experienced associates to high-impact categories and train them to convert urgency into upsells.
• Price and promotion transparency: provide clear, consistent pricing across online and offline channels to reduce friction.

Medium-term actions

• Structure product metadata: implement standardized product feeds (titles, attributes, certifications, return policies) to improve discoverability for AI tools.
• Integrate payment options: support common digital wallets, tokenization and seamless checkout flows to lower abandonment risk.
• Build partnerships: enable API access for curated marketplaces and vetted agent platforms seeking reliable supply partners.

Long-term actions

• Prepare for agentic commerce: define terms and APIs that allow trusted agents to transact on behalf of customers while protecting margin and brand integrity.
• Invest in personalization with guardrails: use AI to tailor offers without eroding margins or violating customer privacy.
• Monitor fraud and return risks: automated purchasing increases attack surfaces; adaptive fraud detection and nuanced return policies become more important.

Consumer Considerations: Privacy, Control and Subscription Dynamics

AI power users often pay for subscriptions because the tools yield value. That payment signals trust in the service, acceptance of data sharing, or desire for higher-quality outputs. However, consumers should weigh benefits against risks.

Privacy and control

• Data collection: paid AI services typically collect behavioral and preference data to personalize recommendations. Consumers should evaluate privacy policies and opt-out choices.
• Consent and transparency: consumers need clear explanations of how their agents make choices, especially when agents can commit funds or execute purchases automatically.

Subscription economics

• Cost-benefit analysis: the value of paid AI depends on shopping frequency, average basket size and time saved. Heavy holiday shoppers or frequent gift buyers may realize immediate ROI; occasional buyers may not.
• Vendor lock-in: personalized AI agents may lock users into ecosystems. Consumers should consider portability and the ability to revoke access.

Security

• Payment safety: agentic purchases that store credentials or use frictionless payment raise security stakes. Consumers should use services that implement tokenization and multi-factor protections.
• Fraud red flags: consumers should verify unusual transactions quickly and understand dispute procedures for agent-initiated purchases.

Small Business and Boutique Strategies to Capture AI-Driven Demand

Independent jewelers, boutique handbag makers and specialty cosmetics brands can capture AI-driven shoppers by taking practical steps that improve discoverability and trustworthiness.

Make product data agent-friendly

• Standardize metadata: include clear titles, dimensions, materials, certifications (e.g., GIA for diamonds), and high-resolution images.
• Include policies: explicit return, warranty, and shipping policies help agents assess risk.

Be present where agents look

• Register with curated marketplaces: being part of trusted platforms elevates visibility.
• Emphasize reviews and provenance: verified customer reviews, third-party certifications, and provenance data are reliable signals for agent evaluation.

Streamline fulfillment and service

• Offer rapid fulfillment options and clear cutoffs for holiday delivery.
• Provide concierge-level service: engraving, gift-wrapping, and certificate documentation create value agents can relay to buyers.

Experiment with AI tools

• Use generative tools for product descriptions and imagery, then validate outputs for accuracy and compliance.
• Adopt AI-driven customer service to handle last-minute inquiries and reduce friction during peak weeks.

Fraud, Chargebacks and Trust in an AI-Driven Marketplace

As agents execute transactions, fraud risk evolves. Automated purchasing can increase velocity and scale of attacks if safeguards lag. Retailers and payments providers must adapt.

Fraud prevention measures

• Behavioral analytics: monitor purchase velocity and atypical account actions in real time.
• Authentication friction: apply stepped-up authentication for high-value or unusual transactions while preserving frictionless experiences for verified users.

Dispute resolution

• Clear policies: explicit policies regarding agent-initiated orders and delegate purchases help customers and merchants resolve disputes more quickly.
• Cooperative frameworks: payment networks and marketplaces should establish protocols that distinguish between user-authorized agent purchases and fraudulent activity.

Trust-building

• Transparent seller badges: third-party vetting and badges can help agents evaluate seller reliability quickly.
• Post-purchase support: robust return and repair processes reduce buyer anxiety around high-value last-minute purchases.

Examples of AI-Assisted Holiday Use Cases

The theory is useful, but concrete examples show how behavior shifts.

Example 1: Family Gift List Management A busy parent subscribes to an AI assistant that maintains separate gift lists for friends and family, monitors price drops, and automatically purchases when items fall within target price bands. The assistant bundles shipments to reduce delivery costs and schedules gift-wrapping with the selected merchants.

Example 2: Multi-Stop Travel Planning A couple wants a holiday weekend trip. Their AI agent checks flights, cross-references hotel loyalty benefits, books a rental car, and aggregates travel insurance. For purchases it cannot finalize automatically, the agent sends a choice set to the couple with a one-tap payment link.

Example 3: Jewelry Sourcing and Authentication A buyer wants a vintage-inspired ring with a specific setting. The agent queries boutique jewelers, checks certifications and photographs, and requests additional images via direct messaging. When the buyer approves, the agent initiates purchase with an escrow-like payment arrangement to protect both parties.

Each use case shows a common thread: customers delegate complexity and execution to tools that provide speed, trust and convenience.

Competitive Risks and Market Dislocations

AI-driven commerce will reweight advantages across the retail ecosystem. Anticipate these shifts:

Winners

• Retailers that provide clean, structured data and consistent fulfillment.
• Curated platforms that establish themselves as trustworthy intermediaries for agents.
• Independent sellers who can articulate provenance and offer unique value.

Losers (or challenged)

• Sellers with inconsistent product descriptions, erratic inventory and slow fulfillment.
• Merchants who rely on opaque or platform-specific promotions that agents cannot parse.
• Businesses unwilling to adapt their systems to agentic queries.

Market dislocations could also arise if agents concentrate purchasing power toward a small set of intermediaries. That concentration could compress margins for sellers and concentrate fees in the hands of a few agent platforms—replicating marketplace dynamics seen in prior platform waves.

Measuring Success: KPIs for an AI-Influenced Holiday

Retailers should monitor metrics that reflect both channel performance and agentic readiness.

Revenue and volume

• Revenue growth (nominal and real): disaggregate price-driven growth from unit growth.
• Conversion rates: online and in-store conversions from discovery to purchase.

Operational

• On-time fulfillment rate and delivery accuracy.
• In-store pickup rates and same-day delivery volumes.

AI-specific

• Share of transactions initiated or completed via AI tools or agents.
• Merchant visibility in agent queries (search impressions, discovery events).
• Rate of agent-driven returns and disputes.

Customer experience

• Net Promoter Score and satisfaction metrics for post-purchase service.
• Time-to-purchase from initial discovery.

These KPIs give retailers the ability to spot whether their strategies are capturing AI-influenced demand or merely absorbing higher price signals.

Regulatory and Ethical Considerations

Agentic commerce and paid AI subscriptions raise regulatory questions. Policymakers will focus on transparency, consumer protection and competition.

Transparency and disclosure

• Agents must disclose when they act on behalf of users and when promotions or affiliate relationships bias recommendations.
• Sellers and platforms must provide clear information about return rights, warranties and escrow protections for high-value goods.

Competition and market power

• Antitrust regulators may scrutinize any concentration of agent access that limits merchant visibility.
• Platforms with both agent and merchant functions face potential conflicts of interest that require oversight.

Consumer protection

• Standards for agent authorization and revocation will be necessary to prevent unauthorized charges.
• Dispute resolution pathways must be established that account for intermediated purchases.

Ethical design

• Agents should avoid exploiting vulnerable users or nudging them into purchases inconsistent with stated budgets.
• Developers must build privacy-preserving defaults and easy consent revocation.

The regulatory environment is likely to evolve rapidly; retailers that prepare compliance workflows now will face fewer operational disruptions later.

What This Means for Holiday 2026: Practical Takeaways

Consumers: If you subscribe to paid AI services, you may find yourself shopping earlier and across a wider set of merchants. Weigh the subscription cost against your shopping frequency and value capture. Pay attention to agent permissions and monitor transactions closely during peak weeks.

Retailers: Ensure your data and fulfillment systems are coherent. Offer clear last-mile assurances and craft policies that make your products attractive to AI agents and the shoppers who use them.

Small businesses: Structured metadata and trustworthy reputations matter. An investment in clear product descriptions, verified reviews and expedited fulfillment pays disproportionately when agents surface your listings to high-intent shoppers.

Payments and platforms: Prepare for agentic workflows by enabling secure, tokenized payment flows and building dispute mechanisms tailored to delegated purchasing.

Across the market: The headline 5.5% growth figure masks nuance. Half the dollar increase reflects higher prices; online growth will outstrip in-store gains; and AI power users will shape where and when much of the incremental spending lands. Businesses that treat AI as an operational imperative — not just a marketing angle — will be better positioned to convert intent into transactions.

FAQ

Q: What exactly defines an "AI power user" in Mastercard’s analysis? A: Mastercard classified AI power users as consumers who subscribe to paid AI services. The designation serves as a behavioral proxy for individuals who actively use AI tools, which correlates with different shopping timing, merchant diversity and category preferences.

Q: Is the projected 5.5% growth driven by more items being sold or just higher prices? A: Approximately half of the projected increase reflects higher prices. That means nominal spending growth is heavily influenced by price levels; unit volume growth is likely smaller. Retailers should distinguish between revenue gains and market-share gains.

Q: How will agentic commerce change holiday shopping this year and in the coming years? A: Agentic commerce will streamline discovery-to-purchase flows by allowing AI agents to search, compare and potentially execute purchases on behalf of users. Mastercard projects widespread adoption by 2030, with over 300 million online shoppers using agents regularly. Short term, expect more efficient, earlier buying among subscribers; mid term, retailers will need agent-ready metadata and APIs to remain discoverable.

Q: Which product categories are most affected by last-minute shopping patterns? A: Jewelry, handbags, department stores and cosmetics showed significant last-week-of-season spikes in 2025. High-value and gift-centric categories tend to see pronounced late-week buying, often because customers seek in-person verification or last-minute high-impact gifts.

Q: What should small jewelers and boutique retailers do to capture AI-driven shoppers? A: Standardize product metadata, provide clear shipping and return policies, secure verified reviews and provenance information, and ensure accurate, real-time inventory. Offering rapid fulfillment and concierge-level services increases appeal to both human shoppers and AI agents.

Q: Are there heightened fraud risks with AI or agent-assisted purchases? A: Yes. Automated purchasing can magnify fraud velocity and scale. Retailers should invest in behavioral analytics, adaptive authentication for high-risk transactions and robust dispute resolution processes. Tokenized payments and secure credential storage mitigate some risks.

Q: Will AI favor large retailers over small ones? A: Not necessarily. AI tends to surface sellers that meet agent criteria: structured data, reliable fulfillment, clear policies and strong reputations. Small sellers that meet these standards and offer unique value can be favored by agents. Conversely, merchants with poor metadata and slow fulfillment risk invisibility.

Q: Should consumers cancel paid AI subscriptions for holiday shopping? A: Decision depends on individual shopping behavior. Frequent shoppers or those who value convenience and curated discovery may find subscriptions worthwhile. Casual shoppers may benefit from trial periods or pay-as-you-go options. Regardless, consumers should monitor permissions, transaction logs and privacy settings.

Q: How can retailers measure whether AI-influenced shoppers are affecting their sales? A: Track AI-specific signals such as referral sources from AI tools, conversion rates for traffic labeled as AI-origin, share of transactions with agent authorization tokens, and changes in merchant discovery metrics. Correlate those data with inventory turns and customer LTV to determine strategic impact.

Q: What policy changes should businesses watch for as agentic commerce grows? A: Expect regulation around transparency of agent recommendations, consumer authorization protocols, dispute resolution norms for delegated purchases and potential antitrust scrutiny if agents consolidate marketplace access. Businesses should build compliance-ready processes now.

Q: How can consumers protect themselves from unwanted agent-driven purchases? A: Use explicit authorization controls, require confirmations for purchases above a threshold, enable transaction alerts and keep payment methods isolated for agent use. Regularly review the agent’s activity log and revoke permissions when necessary.

Q: Are there environmental or sustainability implications tied to AI-driven holiday commerce? A: Faster discovery and more targeted purchases could reduce returns, which lowers unnecessary shipping. However, agent-driven speed and last-minute delivery preferences may increase expedited shipments, which are more carbon-intensive. Retailers should balance convenience with sustainable fulfillment options.

Q: What is the single most important action retailers should take before the holiday surge? A: Ensure inventory accuracy and fulfillment commitments are reliable across channels. That operational foundation determines whether omnichannel shoppers and AI agents convert into successful transactions during peak demand.

Q: How definitive are Mastercard’s projections? A: Mastercard’s forecast synthesizes transaction data and macroeconomic indicators. Forecasts are probabilistic and subject to shifts in economic conditions, supply chain disruptions, and consumer sentiment. Use the projections as directional guidance rather than absolute outcomes.

Q: How will loyalty programs interact with AI-driven shopping? A: Loyalty programs that are machine-readable and integrated into agent workflows will retain advantages. Agents can surface loyalty benefits, points optimization and personalized offers if retailers expose those perks through APIs or structured offers.

Q: Will agentic commerce replace traditional shopping? A: Agentic commerce will extend and expedite many tasks, but it is unlikely to eliminate traditional buying. Physical experiences, social commerce and impulse purchases still have roles. Agents will capture routine, high-efficiency workflows; human-led discovery and experiential retail will persist.

Q: If I'm a consumer worried about price increases, how should I approach holiday shopping this year? A: Start by prioritizing gifts and categories with the highest personal value. Use price-tracking tools to identify deals without over-searching. Consider staggered purchases to hedge against volatility and look for bundled services (warranties, expedited fulfillment) that add certainty during holiday timelines.

Q: How can merchants test agent readiness without major investments? A: Begin by auditing product feeds for completeness, improving image quality and standardizing return and shipping policies. Participate in curated marketplaces that offer agent exposure and pilot integrations with a single agent platform to measure incremental discovery benefits.

---

Mastercard’s forecast signals more than a seasonal uptick; it indicates a maturing intersection between consumer finances and emergent AI behaviors. Online growth, agentic capability, and last-minute purchase dynamics each present distinct operational and strategic challenges. Merchants that align infrastructure, data and customer trust will capture incremental spend more effectively. For consumers, subscriptions and agents promise convenience — but require vigilance about control and costs. The holiday season will be a testing ground for these trends; outcomes this year will shape how retailers and shoppers adapt to an increasingly automated marketplace.