As OpenAI expands ChatGPT’s commerce capabilities through partnerships with Shopify, Walmart and PayPal, a quiet transformation is underway. The platform is becoming a shopping interface that can recommend products, manage checkout and connect transactions directly to fulfillment.
That shift has created an industry divide. On one side are the innovators experimenting with AI-driven commerce. On the other are the brands holding back, waiting for more clarity or control. The hesitation is understandable. But in a world where digital markets tend to reward the first movers, waiting is not cautious. It’s risky.
We have seen this dynamic before. In digital ecosystems, the rule is often winner takes most. Amazon, Spotify and Uber each dominate their categories because early adoption created an unbeatable flywheel of data, visibility and user trust. The same pattern is now emerging in AI commerce. As AI agents become the new gatekeepers of discovery, the brands that move first to optimize for this shift will own a disproportionate share of voice, and ultimately a disproportionate share of wallet.
Inside the AI Commerce Split
OpenAI’s commerce integrations are moving faster than most brands expected. Many consumer product companies are eager to explore what is possible, while others are pausing, worried about losing control over how AI platforms represent their brands. But the algorithm is already speaking for brands.
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When shoppers ask ChatGPT or other generative AI search tools for “the best sunscreen” or “a sustainable detergent,” an answer appears whether or not the brand has shaped it. In that moment, brand perception is defined not by the marketing team, or the retailer, but by data quality, accessibility and machine readability of all online content.
Why Waiting Means Vanishing
Publicis Sapient’s Guide to Next 2026 report reveals that most consumer-product companies are unprepared for this new dynamic:
- Only 37% of brands run a monthly audit of how AI assistants describe them, while 25% do so just once a year.
- Just 33% say their product data is consistent across channels.
- Only 36% report that their data is fully structured and machine-readable.
These numbers reveal a quiet visibility crisis. Many brands have already lost control of the “AI shelf,” the digital layer where algorithms, not humans, decide what gets recommended or ignored.
Refusing to engage with ChatGPT commerce out of brand control fears will not prevent that loss; it accelerates it. If product data is not findable, structured, consistent across channels and reflective of brand values, AI assistants will simply skip over the brand in favor of competitors that are better prepared.
Turning AI Disruption Into Advantage
Agentic commerce, where AI agents act on behalf of both consumers and brands, represents a once-in-a-generation reset. It is an opportunity to rebuild visibility from the ground up, ensuring that brand identity and proof points are expressed clearly in the data powering algorithmic discovery.
For the first time in decades, the playing field is shifting. Success will depend less on advertising spend and more on how clearly a brand’s digital footprint communicates who it is. The next advantage will not come from who shouts loudest, but from who is most legible to machines.
Even as AI removes traditional gatekeepers like retailers, new ones are already forming: aggregators that scrape brand data and insert themselves between you and your customers. Without a clear Agent Experience (AX) strategy, brands may simply swap one middleman for another.
Three Moves Every Brand Should Make
1. Treat training data as your new media buy: In traditional media, brands pay to reach audiences. In AI commerce, the investment is in making sure the information those systems read and process is accurate, structured, and current. Audit how your products appear in AI-generated responses. The next frontier of brand visibility is not a banner ad. It is a clean, complete data feed that tells AI systems who you are.
2. Build for bots, not billboards: Every brand has a tone, a purpose and a set of values. In agentic commerce, those must be encoded into data itself. Define the metadata and structured attributes that communicate what matters most, such as quality, sustainability, service or trust. If your data does not include the evidence behind your promise, algorithms cannot recognize your distinction.
3. Balance AX (Agent Experience) and CX (Customer Experience): AX is how well your data connects with AI systems; CX is how well your story connects with people. Building a great AX ensures your brand appears in the consideration set. Investing in both experiences, algorithmic efficiency and emotional resonance, will define tomorrow’s retail leaders.
Looking Ahead
AI commerce is happening now. Waiting for perfect clarity or control means letting algorithms define your brand without you. The opportunity is to act deliberately: organize data, define brand signals and design for a world where visibility depends less on ad spend and more on clarity and credibility. Agentic commerce will reward the brands that move early, with purpose and precision built into their data.
Simon James is the Global VP of Data Science and AI at Publicis Sapient. He leads a specialist team spanning Data Strategy, Data Science, Data Engineering and Digital Analytics, supporting Publicis Sapient’s clients across the globe. In this role, James ensures that clients’ data- and AI-driven transformation programs are successfully executed end to end. Helen Merriott is SVP, Consumer Products Lead at Publicis Sapient, with a focus on EMEA and APAC. She joined Publicis Sapient in 2023 after an executive career at Google, Accenture, and EY, where she spent 30 years designing and leading major digital transformation programs. With a background in strategy and consulting, she is passionate about technology-enabled transformation that delivers measurable outcomes for consumers and citizens.
