From Circulars to Shopping Agents

Welcome to Marketecture! Today, Marketecture’s Jackelyn Keller examines what happens when brands must appeal not only to consumers, but also to the AI agents acting on their behalf.

Last Tuesday, after Labor Day weekend, my daughters went back to school, starting second and fourth grade. In the weeks leading up to it came the usual lists, sneakers, backpacks, supplies, and a few must-haves that definitely weren’t on the school list, including NeeDohs repurposed as sneaky little fidget tools.

Somewhere in the middle of all that shopping, I started thinking about how different back-to-school looks from when I was a kid. Back then, you scanned the Sunday circular, spotted the giant BACK TO SCHOOL sign in a store window, piled into the car, and went looking for what you needed. Advertising had a pretty straightforward job: show us the products, give us a reason to want them, maybe throw in a sale. It could influence the decision, but we still did the shopping.

That has been changing for decades, but AI is accelerating it. And that shift is already showing up in how parents shop. In fact, a June 2026 study from PwC found that 73% of parents plan to use AI somewhere in this year’s back-to-school shopping journey, from researching brands and comparing products to budgeting and finding deals.

The first big shift wasn’t that technology started shopping for us. It started learning from how we shopped. Search captured what we were actively looking for. Cookies remembered what we browsed. Recommendation engines learned what people with similar behaviors tended to buy next. And retargeting made sure the backpack we looked at once could follow us around the internet until we bought it, or finally cleared our cookies.

Programmatic made all of that behavioral data actionable at scale. Instead of broadly assuming that “parents buy school supplies,” marketers could use behavioral, contextual, commerce, and identity signals to determine which shopper to reach, with which product, in which moment, and at what price.

The ad formats evolved right along with the machinery behind them. Static banners became dynamic product ads. Product feeds could swap images, prices, and offers. Recommendation engines could rank thousands of products differently for different shoppers, while DCO adapted creative based on audience, context, and performance. We were still doing the shopping, but increasingly, technology was deciding what made it into our consideration set.

Today, those systems don’t just react to what we searched for yesterday. First-party purchase data, retailer signals, browsing behavior, content consumption, timing, price sensitivity, and countless other inputs can help marketers anticipate what we might want next.

Our behavior leaves behind a lot of clues. Taken together, those signals can reveal not just what we’ve done, but what we value, what motivates us, and what we may be likely to do next. AI is making it easier to turn that understanding into action.

You can see that shift in the creative itself. For years, DCO often meant swapping a background, changing a CTA, or dropping in a location and calling it personalization. Useful? Sure. Magical? Not exactly. But the underlying idea was always bigger: that the same product could be presented differently depending on who was seeing it and what the system predicted would resonate.

Creative can now be generated, versioned, and adapted faster. Products can be selected dynamically. Copy, imagery, and offers can shift based on context, audience, and performance. The goal is no longer just to target a shopper. It’s to predict which message, which framing, or which version of the product is most likely to move them.

“The biggest change isn't how much data we have about a shopper. It's what creative can do with it,” shared Priti Ohri, Co-Founder & CEO of Advertible. “For years, data determined who saw an ad. Today, it helps shape the creative itself. That also means ad formats have to evolve from static assets into adaptive experiences that can respond in the moment."

Conversational AI changes something even more fundamental: the input. A search query might say “girls backpack.” A prompt can say, “Find me a durable purple backpack for a fourth grader, under $60, with room for a Chromebook, that can arrive by Friday. No giant logos.”

That one prompt contains product intent, shopper context, budget, use case, aesthetics, and logistics. It’s practically a creative brief. And ad formats are already adapting to that richer context. Criteo’s Prompt Smart Ads, for example, use catalog data, commerce intelligence, and prompt-level insights to tailor ad creative and product descriptions to what a consumer is actually asking.

This is where agents start to feel especially useful to me. I’d happily hand off the predictable parts of back-to-school shopping: find the options, compare prices, check the requirements, get it here on time. Let an AI agent handle that. I’d rather keep the parts that become memories, like taking my girls shoe shopping and recreating the very specific Payless ShoeSource ritual I still remember from childhood.

Consumers seem to be drawing a similar line between help and autonomy. Gartner found that only 11% of U.S. consumers are ready to let AI actually make purchase decisions on their behalf. We’re increasingly comfortable outsourcing the work before we’re ready to outsource the final decision.

“We watch agents researching products, comparing options, putting the right item in the cart, then handing off to a human who swoops in and completes the purchase,” explains Becky Gundy, Head of Global Marketing at CHEQ. “That handoff is getting more and more common, but it's also temporary. Soon agents will be able to buy on your behalf, start to finish. They're not just going to influence commerce, they're going to participate in it.”

That handoff may be the transitional phase we’re in now.

And the ad format changes again. In an agentic environment, advertising may look less like a banner and more like a sponsored recommendation, tailored offer, or product suggestion surfaced inside the conversation itself.

For marketers, that raises a new question: What happens when we need to be chosen not only by the consumer, but by the consumer’s agent?

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