Holiday shoppers have long turned to search engines and online marketplaces to find gifts, compare prices, and hunt for deals. This year, more of them may have some help from AI.
AI shopping agents are evolving from tools that simply recommend products into assistants capable of handling more of the shopping process — comparing options, working within a budget, checking availability, and helping consumers make purchasing decisions.
For small retailers, that creates both an opportunity and a challenge: An AI agent could introduce your business to a customer who might never have found it otherwise — but only if the agent can understand what you sell, what it costs, whether it’s available, and how customers can get it.
I talked to Sean Turner, CTO and co-founder of Swiftly, about how AI shopping is changing and what small retailers can do now to prepare for the holiday season.
How AI Shopping Agents Are Changing Holiday Retail
Rieva Lesonsky: What has changed about AI shopping agents that makes this holiday season different from last year? What are consumers actually able to delegate to AI today?
Sean Turner: What makes this holiday season different is that AI is starting to move beyond answering shopping questions and into handling more of the shopping journey for consumers. A year ago, shoppers were primarily using AI to research products, compare options, or get recommendations. Today, agents are getting better at handling multi-step tasks, like narrowing products based on a budget, comparing options across retailers, building a shopping list, and helping shoppers move closer to a purchase.
This is helpful during the holidays, when consumers are juggling tighter budgets, longer lists, promotions, availability, and timing. AI can help reduce some of that friction while also creating a more personalized shopping experience. If an agent understands what a shopper typically buys, their price sensitivity, dietary needs, or preferred brands, it can help them navigate the season in a way that feels more relevant to them.
This is one of the things I find most exciting about AI for smaller retailers. It can give a smaller team capability that historically required much larger budgets, teams, and technology investments. For smaller retailers operating on tight margins, getting one more trip or one more item from an existing customer can be just as important as acquiring a new shopper.
Lesonsky: For a small retailer, where could AI agents have the biggest impact this holiday season: product discovery, comparison shopping, recommendations, purchasing, or somewhere else?
Turner: The biggest opportunity for small retailers using AI agents this holiday season is personalization. Specifically, using AI agents to understand individual shoppers and determine what offer or product is most likely to create engagement.
Retailers already have massive amounts of first-party data about their customers and their purchasing behavior. Rather than relying on broad promotions, retailers can use AI to analyze that data and tailor products, offers, and messages to individual shoppers, delivering 1:1 personalization at a scale that isn’t possible manually.
That matters when marketing budgets are limited and margins are tight. During the holidays, shoppers are being hit by multiple promotions and making more frequent decisions around budgets, promotions, and last-minute needs. AI can help retailers make these interactions more relevant, driving immediate sales while giving customers a stronger reason to come back.
Lesonsky: If consumers increasingly rely on AI to find and compare products, what information does a retailer need to make easily accessible so an AI agent can accurately understand its products, prices, availability, shipping, and return policies?
Turner: Retailers should think about how clearly and consistently their digital systems describe what they sell and how someone can buy it. That starts with accurate product names and descriptions, current pricing, inventory availability, promotion details, shipping or pickup options, and return policies.
Personalization also depends on having strong data foundations. An agent cannot make a useful recommendation if it does not understand whether a product is actually available, what it costs, or how it compares with a shopper’s preferences and past behavior.
Consistency matters a lot here. If a price appears differently on a product page, in an app, and in a product feed, or if a promotion is represented differently across channels, an AI agent may struggle to determine what is actually true. During the holidays, when inventory and promotions can change quickly, stale or inconsistent information can lead to a poor recommendation at exactly the moment a retailer is trying to win that shopper’s business.
Lesonsky: You say retail-specific context matters. What might a general-purpose AI agent misunderstand about promotions, inventory, margins, or shopper behavior, and what could that mean for a small retailer?
Turner: Retail-specific context matters because knowing the product isn’t the same thing as understanding the business of retail. A general-purpose AI agent may understand what a product is, but not necessarily the economics or behavior behind the purchase.
Take promotions, for example. A discount may look attractive from the shopper’s perspective, but for the retailer, the value of that promotion depends on things like inventory levels, margin, vendor funding, and what else tends to land in the basket. In grocery, where retailers often operate on very thin margins, a recommendation that drives volume but erodes profitability is not necessarily a good outcome.
Inventory is similar. Knowing that a product is technically available does not tell you whether it is available at the right location, in enough quantity, or at the moment the shopper needs it. A retailer may also know that a customer who buys one holiday item is highly likely to buy several complementary products, which can influence what a useful recommendation looks like.
For a small retailer, those nuances can have an outsized impact. A poorly informed recommendation can mean a lost sale, lower margin, or a frustrating customer experience. A well-informed one can increase basket size while also making the shopper feel understood.
Lesonsky: Could AI shopping agents make it harder for smaller retailers to compete with large brands and marketplaces, or could they actually make smaller businesses easier to discover? What will determine which happens?
Turner: AI shopping agents could make smaller retailers easier to discover, but a lot depends on whether those retailers give agents enough accurate information to work with.
Large marketplaces have an advantage because they already have enormous amounts of structured product and transaction data. But AI also has the potential to change how consumers discover products. A shopper may no longer start with a specific retailer or brand. They may simply ask for the best option based on their budget, location, preferences, or timing.
That could create an opening for smaller retailers. If an AI agent can clearly understand what they sell, what is in stock, what it costs, and why it is relevant to a specific shopper, they have a better chance of being surfaced alongside much larger competitors.
AI can help on the retailer side too. If it can help a smaller team analyze more data, personalize more interactions, and execute work that previously required a much larger organization, that’s a real competitive advantage.
Lesonsky: What mistakes are retailers making as they prepare for AI-driven shopping? Are businesses focusing on adding AI tools when they should be fixing something more fundamental first?
Turner: One of the biggest mistakes retailers are making as they prepare for AI-driven shopping is treating AI readiness as a software purchasing decision.
The technology is only as good as the product, pricing, inventory, and customer data it can access. You can deploy the best AI model in the world, but if it doesn’t understand your business, it’s going to struggle to make good decisions. Before adding another AI tool, retailers should ask some more fundamental questions. Is the product information accurate? Are promotions represented consistently across channels? Can we reliably tell what is in stock? Do we have enough customer context to make recommendations that are actually relevant?
Those fundamentals become even more important during the holidays because the cost of getting something wrong is higher. Inventory is moving quickly, consumers are more price-sensitive, and retailers are competing for loyalty during one of the busiest periods of the year.
The goal should be to use AI in a way that helps create a better customer experience and a better outcome for the retailer.
Lesonsky: If you’re a small retailer with limited time and money, what three things should you do before the holiday shopping season to make your business more ready for consumers using AI agents?
Turner: If I were a small retailer with limited time and money, I would focus on these three things before the holiday shopping season.
First, clean up your core product data. Make sure product descriptions, prices, availability, and key attributes are accurate and consistent wherever shoppers might find you. If an AI agent cannot confidently understand what you sell, it cannot confidently recommend you.
Second, make the buying experience clear. Shipping timelines, pickup options, holiday promotions, and return policies should be easy for both consumers and AI systems to understand. During the holidays, convenience and certainty can be major drivers of where someone chooses to shop.
Third, focus on personalization where it can have the greatest impact. You do not need to automate every part of the customer journey. Start with a few areas where better context can make shopping easier, such as helping someone find the right product, suggesting a relevant substitute when something is out of stock, or recommending complementary items based on their needs.
For smaller retailers, every customer relationship matters. The goal isn’t to use AI everywhere just because you can. It’s to identify where AI can remove friction, make the experience more relevant, and help the business operate more effectively. If you can do that without sacrificing margin, you’re not just setting yourself up for a stronger holiday season — you’re building a better customer relationship for the long term.
My Takeaway
Small retailers don’t need to become AI experts before the holidays. But they do need to make sure AI shopping agents can understand their businesses.
That means getting the basics right: accurate product descriptions, up-to-date prices and inventory, clear shipping and pickup information, and easy-to-find return policies. If that information is inconsistent or outdated, an AI agent may overlook your business or, worse, give a potential customer incorrect information.
The opportunity is significant. AI shopping agents could give smaller retailers a new way to be discovered by consumers who aren’t searching for a particular store or brand. But before you invest in another AI tool, make sure the information you already have is ready for the AI-driven shopping world.
Rieva Lesonsky is the founder of Small Business Currents, a content company focusing on small businesses and entrepreneurship. You can find her on Twitter @Rieva, Bluesky @Rieva.bsky.social, and LinkedIn. Or email her at Rieva@SmallBusinessCurrents.com.
Photo courtesy Getty Images for Unsplash+
