When Your Best Customer Goes to AI First
AI tools are becoming the default starting point for product discovery. The brands that consumers choose to engage with directly will be the ones that win loyalty in this shift, and they're building for it now.
Key takeaways
- The competitive frame for retail is shifting. In addition to traditional rivals, brands are competing at the top of the purchase funnel against the AI tools consumers use daily, such as ChatGPT, Claude and Gemini, and for visibility inside them.
- Keeping existing customers means offering compelling enough experiences that they come to you directly instead of their favorite large language model (LLM). Winning new ones is a separate game, decided by your visibility inside AI-driven discovery.
- AI-driven traffic to U.S. retail sites grew 805% year over year on Black Friday 2025. Open commerce protocols, including Google's Universal Commerce Protocol and OpenAI's Agentic Commerce Protocol, connect AI agents directly to retail catalogs.
- Getting ahead requires two reinforcing investments: brand-owned AI experiences that earn loyalty, and catalog visibility and context across AI-powered discovery. Both start with the same clean, structured data foundation.
The benchmark has shifted, and most retail strategies miss it
For years, chatbots consistently ranked lowest in retail experiences. Consumers actively avoided them. That has reversed. Adobe Analytics reported that AI-driven traffic to U.S. retail sites grew 805% year over year. Consumers now expect AI-powered interactions on retail sites to perform at the level of their favorite LLM. It's a new reference point for what a useful shopping experience looks like, and it's reshaping how consumers judge every retailer.
Consumers can ask an LLM a question in plain language, get a curated shortlist in seconds and have it act on their behalf. This is what the industry calls agentic commerce, and it's moving the moment of discovery off the brand's own site. McKinsey projects agentic commerce could redirect $3 to $5 trillion in global retail spend by 2030.
Yet most retailers' strategies don't account for that shift. SEO is calibrated to win search rankings, ad spend converts consumers already in a buying mindset, and loyalty programs deepen relationships with people who've already chosen the brand. None of them address the question: Will a consumer turn to your app or website, or ask an LLM instead?
What the market is telling us
The past 18 months show where agentic commerce has taken hold in retail and where it has not. OpenAI launched Instant Checkout in September 2025, betting consumers were ready to buy directly inside ChatGPT. By March 2026, it pulled the feature back. OpenAI's Agentic Commerce Protocol (ACP) is now focused on helping consumers find and compare options within ChatGPT, then routing them to retailers' own sites to complete the purchase.
At NRF 2026, Google and Shopify launched the Universal Commerce Protocol (UCP), an open, cross-vendor standard codeveloped with Etsy, Wayfair, Target and Walmart, that gives agents a common way to discover, compare and checkout. While adoption is still early, the protocol has already gained significant traction with more than 20 industry partners endorsing it.
The development of these protocols, and others, shifts the question for retail leaders from whether to take agentic commerce seriously to how prepared the brand will be when it scales.
What it takes to compete on this terrain
Addressing this shift requires investment on two fronts that reinforce each other.
The first is investing in brand-owned experiences that are worth returning to: a customer already shopping with you, comparing your own products and deciding whether your experience beats a neutral LLM. An AI-powered experience within a retailer's app or website that knows the consumer, reflects their preferences and solves a problem is one of the strongest responses to AI-neutral shopping behavior.
The second front is catalog and data accessibility. Whether or not a brand builds its own AI capabilities, its products need to be discoverable, descriptive, accurate and well-structured for the AI agents that shop on consumers' behalf.
Treating catalog data, back-end API accessibility and data governance as strategic leadership priorities rather than IT maintenance functions determines how visible a brand is across the AI-powered discovery channels that consumers are increasingly using. It also changes where brand influence operates. When an agent compares on the consumer's behalf, the catalog becomes the primary channel for differentiation. What isn't encoded in the data doesn't exist to the agent. The context of each product (the information that an agent reasons over when it compares) needs its own ongoing management.
Both fronts rest on the same foundation of clean, unified data. Retailers investing in this foundation in 2026 will be better positioned when competitive pressure peaks.
What retailers should do now
Capgemini research shows that only 2 percent of organizations have deployed agentic commerce at full scale. The window to build a competitive advantage in this shift is open, but narrowing as the broader market catches up. Here are four areas to prioritize now:
- Make data readiness a board-level investment priority. The same data foundation that enables personalization enables catalog visibility in AI-powered discovery. Brands that prioritize it now move faster when expectations accelerate.
- Connect your catalog to where AI discovery happens. Google's UCP and OpenAI's ACP have emerged as two of the leading open standards, though other competing protocols remain in play. Accurate, complete product representation across these channels is the contemporary equivalent of strong search rankings, with the added advantage that early visibility in AI-mediated discovery is still a differentiator.
- Lead with the experience. Consumers do not need to know AI is powering an interaction. They need to feel the brand knows them and the experience is worth coming back to. Any moment that undermines that continuity, such as an unexpected context shift or a response that ignores prior preferences, erodes trust faster in a commerce environment than anywhere else.
- Start narrow and prove the model. The retailers building effective brand-owned AI experiences are starting with one high-friction moment, investing deeply in that use case, validating business impact and expanding from there. Starting broad on a weak data foundation produces the kind of underwhelming experience that pushes consumers toward neutral AI rather than building brand loyalty.
Get started
In our work with retailers, most organizations sit at a 2 on a 10-point data maturity and governance scale. That readiness gap is why a broad, AI-everywhere rollout tends to stall, and why a narrow, well-scoped starting point matters more than ambition. We can help you pinpoint where to start, define the minimum data and architecture requirements, tie it to measurable business outcomes, and prove the model before scaling.
The brands that move first, and move deliberately, will earn the loyalty that defines what comes next.
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This report is compiled from surveys WWT Research conducts with clients and internal experts; conversations and engagements with current and prospective clients, partners and original equipment manufacturers (OEMs); and knowledge acquired through lab work in the Advanced Technology Center and real-world client project experience. WWT provides this report "AS-IS" and disclaims all warranties as to the accuracy, completeness or adequacy of the information.