This holiday season, AI agents are fundamentally changing how consumers discover and purchase products—and most brands aren’t prepared for what they’re losing in the process. While retailers celebrate AI shopping tools that promise convenience and personalization, they’re overlooking a critical reality: these platforms are systematically dismantling every touchpoint where brand value traditionally gets built. The question brands must answer is simple: What’s your brand worth if customers never encounter it?

Listen to “How AI Agents Are Making Brands Invisible” Deep Dive

Last year, shoppers spent over $13.3 billion on Cyber Monday, with growth estimated at 6%, or $14.2 billion, for 2025. Mobile devices will be leading online shopping, with a record 56.1% share of online spend (vs. desktop shopping).

In the current state of marketing—i.e., where websites have been meticulously designed with the user experience and customer journey in mind and optimized for search, and where push marketing strategies are executed through social channels and retargeting is based on search, email marketing or digital ads that are designed to engage and convert—brands can control the journey, from discovery through conversion.

In the world of agentic AI, which is starting to take shape now, AI agents bypass one key aspect of the customer journey by killing any hope of the user landing on the home page. They’re doing this by directing the user to deeper pages that best align with the user’s prompt, bypassing the home page entirely. Is your website even ready to handle a prospect landing deeper into your site?

“The question is: What happens when AI completes the transaction without a human ever seeing your brand name or website?

 

More importantly—what is your brand worth if customers never encounter it?”

Just in time for Black Friday and Cyber Monday, OpenAI released shopping research in ChatGPT, where consumers can be more descriptive about the product they are looking for. As explained by the company, a user types in a query, such as “I need a gift for my four-year-old niece who loves art,” and shopping research puts together a thoughtful guide to help you decide. It asks smart clarifying questions, from investigation through checkout, by researching deeply across the internet, reviews quality sources, and builds on ChatGPT’s understanding of you from past conversations and your ChatGPT memory to deliver a personalized buyer’s guide in minutes.

Late last year, Perplexity rolled out their own AI shopping tool, “Perplexity Buy with Pro,” designed to put the shopper first. As reported, “Instead of promoting products that bring in affiliate money, the platform will recommend items that fit each shopper’s needs, based on past chats and their preferences.” In the results page, the product cards carry an image with pricing, delivery and website details. The platform provides curated reviews and recommendations, along with an “Instant Buy” button built in partnership with PayPal that’s expected to eventually support over 5,000 merchants, allowing transactions to complete without users ever visiting brand sites.

Agentic AI shopping is capable of anticipating, personalizing and automating every step of the process to create frictionless, proactive experiences. Adobe reported that during the 2024 holiday season, AI traffic from generative-AI sources increased by 1,300% year over year from November 1st to December 31st.

Agentic AI commerce isn’t just changing how people shop; it’s systematically removing every touchpoint where brand value traditionally gets built, measured and monetized.

This McKinsey study predicts that “by 2030, agentic commerce could drive $3-$5 trillion in global retail revenue, with the U.S. B2C market alone reaching $1 trillion. That’s roughly one-third of all projected online sales.” And this doesn’t even factor in B2B possibilities.

The same study goes on to say that “This isn’t just an evolution of e-commerce. It’s a rethinking of shopping itself in which the boundaries between platforms, services, and experiences give way to an integrated intent-driven flow, through highly personalized consumer journeys that deliver a fast, frictionless outcome.”

Think about the time and resources invested in website optimization, SEO, paid media and social strategies—all designed to control the customer journey from discovery to conversion. Agentic AI is revolutionizing how we discover and purchase, bypassing traditional search and SEO entirely in favor of personalized, conversational AI experiences.

Early estimates project that AI will drive $263 billion in global online holiday sales this year, with $51 billion in the U.S. alone. But these impressive numbers mask a more troubling reality: AI is systematically diluting the financial investments that B2C and B2B brands have spent years building across three critical touchpoints: 1) brand awareness, 2) emotional connection and 3) customer data.

Consider this query: “Show me the best cordless blind options for a kitchen under $100.” Notice what’s missing? Any mention of a brand or retailer. The AI agent researches based purely on these criteria: cordless blinds, kitchen-appropriate, under $100. Only at the end of this process might a consumer encounter a brand name, buried in a list of algorithmically-optimized options. The brand doesn’t get discovered; rather, it gets selected by the algorithm, sight unseen.

The uncoupling of these touchpoints is due to how the AI platforms search. AI-assisted search/shopping (e.g., ChatGPT and Perplexity) relies on high-quality website content, and third-party reviews/discussions are critical. With agentic commerce (autonomous AI agents), a site’s content needs to be machine-readable, structured and accessible via APIs—not just human-readable web pages.

The opportunity: Identify where you can build brand awareness through site content that aligns with the questions your audience and referral traffic ask and that provides answers to AI agents. Investments in brand awareness will be less about a brand name and more about content that speaks to the benefits of what you do and the value of the services that you provide.

But here’s the problem: even perfect content optimization only gets you into the consideration set. It doesn’t guarantee that the AI agent recommends you. And in fully autonomous agentic commerce, where agents negotiate directly with merchant APIs, your content may never be consumed at all. Being discoverable is a given, while being discovered is becoming an algorithmic roulette.

When AI agents evaluate products, they strip away your brand narrative entirely. That carefully crafted story about heritage, craftsmanship, or values? It gets reduced to a feature matrix: specs, price, reviews, availability. The emotional connection brands spent years building—the reason customers choose your brand over cheaper alternatives—disappears into algorithmic optimization. There’s no brand story in a comparison table, no loyalty in a feature-by-feature analysis.

So where does your brand story go? Nowhere. It simply doesn’t factor into the algorithm’s evaluation. When AI agents optimize for “best value” or “highest rated,” emotional brand differentiation becomes irrelevant. Even worse: some AI platforms don’t send users to your site at all. The recommendation happens, the transaction completes, and your carefully designed brand experience never gets seen.

The opportunity: If AI reduces your brand to features and specs, the response is to embed your brand story within those features themselves. This is where Answer Engine Optimization (AEO) becomes critical. Unlike traditional SEO that optimizes for keywords, AEO optimizes for how AI models parse and synthesize information. It means structuring your content to answer not just the initial question (“What are the best running shoes?”), but the follow-up questions AI agents anticipate (“What makes these shoes unique for marathon training?” or “How does their durability compare to competitors’?”). Your sales and customer support transcripts become strategic assets—they reveal the questions real customers ask, which AI agents will also ask.

But here’s the problem: AEO only matters if the AI agent is consuming content. In fully autonomous agentic commerce, where your AI negotiates with the merchant’s AI based on structured product data and APIs, your carefully crafted narrative never gets read. You can optimize your content perfectly for AI comprehension, but if the transaction happens agent-to-agent based purely on features, specs and price negotiation, emotional differentiation becomes architecturally irrelevant. You’re optimizing for a consideration phase that’s being eliminated.

In the pre-AI era, first-party data was the foundation of customer relationships, with every click and marketing interaction across the brand’s channels captured, analyzed and optimized. To understand the value of these relationships, this report by Forrester found that incorporating first-party customer behavioral data into marketing strategies positively impacts customer acquisition costs by 83%, customer satisfaction by 78%, brand awareness by 75%, conversion by 73% and ROI by 72%.

Yet, by 2026, traditional search volume is predicted to drop 25% due to AI. That’s not just a traffic shift—it’s 25% fewer opportunities to capture first-party data. Without access to search patterns, product preferences and conversion signals, brands lose their ability to personalize effectively or make informed strategic decisions. The discovery happens inside AI platforms, not on your site.

McKinsey’s research reveals that 44% of users who have tried AI-powered search now consider it their primary and preferred source for internet searching, compared with just 31% who prefer traditional search. If AI has become the default discovery mechanism and fewer visitors reach your site directly, how do you capture the data needed to build personalized experiences? You don’t know who your customers are, what problems brought them to the search, or what alternatives they have considered.

The loss of customer data compounds across every brand touchpoint. Without knowing your customer’s price sensitivity, purchase patterns, or preferences, you can’t optimize pricing strategy or build loyalty. Each transaction becomes a standalone event rather than part of a relationship. Traditional loyalty programs and incentives relied on knowing your customer and anticipating their needs; bypassing this step makes customer lifetime value impossible to predict or protect.

This is what makes Amazon so formidable. Their Rufus agentic tool doesn’t just guide product discovery, it captures everything. Every question asked, every preference stated and every price comparison made feeds a constantly flowing data pipeline that informs pricing strategy, content optimization and search algorithms. Amazon owns the complete customer journey data. Competing brands just get order fulfillment information.

The opportunity: Start with your core customer base through loyalty programs, subscriptions and memberships that create direct relationships. These customers can become your research panel. Use supervised surveys to understand how they’re using AI to shop, what questions they’re asking and what information they value the most. Use AI to analyze this feedback, identify patterns, and translate insights into content and experience improvements.

But here’s the problem: This strategy only works if customers choose to have a direct relationship with your brand in the first place. When AI agents handle discovery and comparison, many consumers complete purchases without ever knowing which brand they bought from. They just know that the AI recommended the best option for their needs. You can’t build a loyalty program with customers who don’t realize they’re your customers. First-party data strategies assume you have first-party contact. In agentic commerce, that assumption breaks.

What Strategic Options Remain?

Just as I finished writing this post, today’s New York Times reported how shoppers this holiday season have an abundance of AI options to help with their gift lists, highlighting how brands such as Ralph Lauren, Target and Walmart have deployed “chatbots that act as conversational stylists and shopping assistants. That means people who want to find matching pajamas for the family can ask a chatbot to sort through the options, or for a summary of customer reviews of an air fryer.”

The article identifies how AI can make holiday shopping more “personalized, efficient and cost-effective.” “It fundamentally changes how people shop—moving from humans searching for products to A.I. bringing the right products, at the best price, directly to them.”

“AI can make holiday shopping more “personalized, efficient and cost-effective.”

What brands may not be considering is how AI-driven discovery strips away emotional differentiation while empowering platforms to own customer relationships entirely—forcing the brands to make a strategic choice: Adapt your digital presence for AI discovery, or risk losing relevance entirely. The brands that optimize content for how AI agents search, structure product data for algorithmic evaluation and build direct customer relationships, will maintain visibility. Those that don’t will watch their market share erode as AI simply routes customers elsewhere.

A handful of brands with genuine differentiation and loyal customer bases might execute the direct relationship strategy—i.e., building subscriptions, memberships and communities strong enough that customers specifically request them. But this only works if your brand is truly differentiated, not just well-marketed. For most brands, agentic commerce represents the final stage of a multiyear disintermediation that began when AI search killed the homepage.

This isn’t about whether agentic commerce succeeds. It’s already here. The question is whether your brand shows up in the agentic search results at all.

Questions about your AI Content Strategy? Email me here. As always, thank you for reading and/or listening.