When AI Becomes the Holiday Gatekeeper

AI adoption has surged since ChatGPT launched in November 2022, and with it, the role of AI in the holiday shopping journey. Each year, more discovery, more product education, and more consumer decisions are influenced by AI tools, and Adobe’s retail analytics make that clear. This year, the search isn't just AI-powered. It's becoming agentic.

The Narrative Around Agentic Search

The dominant narrative says consumers will soon outsource holiday shopping entirely, sending AI agents to autonomously purchase gifts while they relax by the fire.

That future may come, but it’s not the present.

Right now, agentic behavior looks more like AI-powered research assistants deployed to narrow options, compare features, and aggregate reviews. They then complete the purchase through familiar search channels like Google, Amazon, and even in-store. The agent doesn't close the deal, but it does have a great deal of influence over what is eventually purchased.

The Attribution Blind Spot

This new behavior matters because its impact is almost completely invisible in current attribution methodologies for most brands.

Consider a simple use case: A consumer asks an AI agent to find the best espresso machines under $500. The agent crawls dozens of sites, synthesizes hundreds of reviews, and compares specs and pricing across dozens of sites. Later, the consumer performs a branded search on Google for a model that appeared on the AI-generated shortlist and converts.

Analytics record a branded search win. What they don't capture is that the AI agent selected the brand upstream. This is the attribution gap marketers must now solve for.

Where Agents Will Act Autonomously (And Where They Don't)

Full autonomous purchasing will arrive first for consumables with low emotional stakes and predictable parameters: toilet paper, laundry detergent, paper towels, pantry staples. Replenishment is perfect agent territory. Set it, forget it, restock automatically. But gifting is an entirely different story.

People will absolutely deploy agents to handle the heavy lifting of gift research: evaluating features, checking reviews, validating pricing, even factoring in recipient preferences if that data is available.

But the final decision will remain human since gifts carry emotional weight. People want to feel confident in their choice. They want to see it, evaluate it, maybe even touch an item before they commit.

The agent gets them 90% of the way there. They close the final 10%.

The Importance of Accessibility

It’s more important than ever that brands ensure their sites are accessible to agents for both research and purchase.

Common blockers include heavy JavaScript rendering, complex authentication gates, content hidden behind interactions, and PDF-only spec sheets. These used to be UX frustrations. Now they're agent experience failures that prevent AI systems from collecting the information required to recommend your brand.

If an AI agent can't crawl or extract a brand’s data, it’s less likely to mention that brand in its responses. And if you’re not in the answer, you’re not in the shortlist. This isn't theoretical. Major brands are already effectively invisible to certain agent workflows because of technical barriers. They show up fine in traditional search, but they're mostly absent from agent-generated recommendations.

84% of Brands Are Flying Blind

A recent McKinsey report found that only 16% of brands have any AI search tracking in place. Meanwhile, the same report projects $750 billion in U.S. revenue will flow through AI-powered search by 2028, and half of consumers already use AI search engines intentionally. Given those stakes, the fact that 84% of brands lack visibility into this channel is staggering. You can't optimize what you can’t measure, and more critically, you can't connect AI visibility to downstream conversion without tracking how often and where you’re showing up.

Brands that are beginning to track their AI presence are discovering important insights:

• Segments where a brand has strong AI visibility convert better in traditional search.
• Branded search volume correlates with AI recommendation frequency.
• High-consideration categories show deeper AI-driven research influence.

Those "out of nowhere" branded searches aren't coming from nowhere. They're coming from AI conversations happening upstream every day.

Your Holiday Action Plan

1. Optimize product feeds for conversational AI

Google Shopping feeds were built for keyword matching, not conversational commerce. Now is the time to start enriching your product feed to cover the wide range of prompts that might be relevant. When someone asks an agent "What are the best wireless headphones for working out?" they expect context and nuance which goes beyond the traditional keyword-focused approach to optimizing product titles.

• Use natural language in product descriptions and write like you're talking to a customer, not a search algorithm.
• Fill out every attribute field. "Optional" fields aren't optional when an AI is deciding whether your product matches a prompt.
• Clearly articulate differentiators and intended use cases. Generic descriptions get generic placement.

Think about the questions consumers actually ask and make sure your product data can teach the AI how to answer those questions with your product.

2. Make your site agent-friendly

If agents can't efficiently extract your content, you’re likely to fall out of their recommendations. Brands should audit their technical foundations to eliminate common agent blockers: heavy JavaScript, PDF-only spec sheets, and unnecessary logins.

Turnkey fixes, like pre-rendering AI-accessible versions of your pages, let agents see your content cleanly without disrupting the human experience.

Layer in structured data, comprehensive FAQs, and comparison-ready feature lists. The clearer and more machine-readable your content is, the more likely you’ll be surfaced in AI responses.

3. Map paid and traditional search visibility to AI visibility

Consumers are using AI agents and traditional search together. That means marketers need to look at visibility holistically. Start by comparing where you appear in agentic search with where you appear in traditional search across both paid and organic:

• Strong paid presence but weak AI visibility = an opportunity to optimize upstream content.
• High AI recommendation frequency in certain segments = expect stronger branded search performance (the consumer was influenced before they ever hit Google).

Identify the prompts where you should appear but don’t. Prioritize by search volume and conversion value. Then resolve the content or technical barriers that keep you out of those conversations.

4. Connect AI influence to downstream conversion

The hardest part is connecting the dots. Attribution won’t be perfect, but patterns will emerge. Brands should build hypotheses and monitor correlations between AI visibility and traditional search performance.

Early signal patterns are already emerging: High AI visibility leads to higher conversion in traditional search, whereas low or zero AI presence leads to weak traction no matter how strong the paid strategy.

The goal isn’t a perfect measurement plan. It’s clarity: Where is AI helping you, and where is it hurting you?

What's Actually Changing This Holiday

The shift this season isn't that AI will buy everything for everyone. It's that AI will quietly shape the decisions behind millions of purchases, long before a consumer clicks “add to cart.” Shoppers will still browse Google, Amazon, and store aisles. But the products they look for will increasingly be determined in an upstream conversation with an AI agent.

If you're not intentionally designing for agent accessibility—and not tracking where and when you appear—you're at a disadvantage.

The agentic holiday isn't about robots buying gifts. It's about AI doing the research that determines which gifts humans choose to buy. That research is happening now, it's accelerating, and some brands are completely invisible to it.

That's the opportunity. And the risk.