The future of commerce is autonomous.
Is that something we can all get behind? It’s certainly the message that’s been coming through loud and clear from the likes of PayPal, Visa, American Express et al of late.
According to Ryan McInerney, CEO of Visa, his firm now boasts 150 AI-powered applications, so the direction of travel is clear from his side of the fence:
We believe that AI and agentic commerce will expand our addressable market. We believe we’re in the very early stages of what’s going to be a major adoption curve in payments. I think to get a sense of like how this progresses from here, it’s instructive to look at other kind of major cycles that we’ve been through, whether it was e-commerce or mobile commerce, tokenization, tap to pay.
These innovations and these kind of major forces, they followed a similar pattern. You have an early period where Visa and other players are establishing standards. We’re announcing, launching and shipping new products, then you migrate into the early adoption period of the curve, which ultimately then leads to growing consumer momentum and, ultimately, broad scale.
All of those previously have gone through that and they’ve achieved that broad scale. We don’t think agentic commerce will be any different, but we’re in the very early stages. So you have consumers that are already using AI to shop and then the next phase will be enabling agents to transact on their behalf, whether with or without them in the loop. And that’s where we come in.
Encouraging that critical adoption is key. Back in May at its I/O Developer conference, Google “Universal Cart”, an AI-powered shopping assistant that consolidates your shopping into one place under Google’s Universal Commerce Protocol. One cart, multiple retailers, and which Vidhya Srinivasan, Google’s VP of Ads and Commerce, promised will “make shopping more fun”, encouraging adoption in the process.
Of course, from Google’s perspective, another key factor here is the impact that agentic AI will have on search. This can be viewed in a positive light Google’s Chief Business Officer, when applied to advertising and product search:
I think it’s really important to understand that Gemini [Google’s multi-modal AI assistant] super-charges our ability to understand what people are looking for and match the right ads. So we’re applying Gemini models really across our entire ads infrastructure, whether it’s ads quality, advertising tools, ads and new AI experiences. And we’re really deeply, deeply integrating Gemini into the customer tools to make the campaigns more efficient, which comes on top of this.
Then we have our AI-powered campaigns like AI Max that help advertisers actually adapt and find the opportunities beyond keyword. Again, that’s an ability for us to go deeper and target better, and AI Max continues to unlock we mentioned as billions of net new searches that weren’t really monetizable before.
LLMs encroach on search
According to the recently published annual State of Commerce study from Salesforce, based on a survey of 3,450 commerce professionals and 4,690 consumers, plus behavioral data from more than 1.5 billion global shoppers, nearly 80% of respondents this year report an increase in traffic from a Large Language Model (LLM)-powered search.
That leads 90% of those polled to believe that AI search will become “essential” for product discovery over the next 12 months.
Meanwhile 71% of commerce leaders says that AI is already a core part of their commerce operations. The top five use cases for agentic AI in commerce are autonomous customer service resolution; AI shopping concierges; autonomous replenishment purchasing; autonomous fraud decision-making and intervention; and autonomous merchandizing optimization.
At the same time consumer usage of AI assistants as tools in their overall retail and shopping experience grew by 200% since the 2025 State of Commerce report came out. Alongside this, it’s revealed that the rate of shoppers discovering products through brand-owned properties fell seven percent and traditional search fell 15%.
According to Caila Schwartz, Head of Agentic Commerce Shopper Insights, Salesforce:
AI is re-making commerce from both directions. Customers are discovering products in places brands don’t control — AI assistants, social feeds, delivery apps — and expecting the same personalized experience everywhere they go. At the same time, AI is changing how commerce teams themselves work: how they merchandise, how they fulfill, how they scale. The difference is speed. A customer can adopt AI overnight. A business has more to get right: trusted data, connected systems, teams ready to use them. The ones getting that right now are the ones that will keep pace.
And to get it right and exploit these behavioral trends, sellers need to take three crucial actions to improve their AI search visibility – improve product content quality; creating and optimize content for conversational and question-based queries; and ensure inclusion by submitting data feeds to AI search platforms.
Feedonomics?
Other commerce specialists concur. There’s a revolution going on, argues Christopher Hess, CEO of Commerce.com:
Commerce is undergoing one of the most significant structural shifts in more than a decade…AI is changing how merchants evaluate technology investments and delaying monetization across portions of the industry. At the same time, product discovery is becoming increasingly distributed across marketplaces, retail media, AI search, shopping agents, and other emerging buying experiences, rather than beginning and ending on a merchant’s website.
This is why Product Intelligence becomes so important, he pitches, throwing a new term into the already over-crowded AI lexicon for good value. Welcome to Feedonomics! Hess explains:
AI agents, marketplaces, retail media networks, search engines, and emerging buying experiences all depend on structured, enriched, and continuously optimized product data….Feedonomics is our Product Intelligence layer, helping merchants structure, enrich, optimize, and distribute product information wherever discovery or emerging buying experiences occur.
As commerce becomes more distributed, we believe Product Intelligence is becoming foundational infrastructure for modern commerce. That is why Feedonomics has become such an important part of our strategy. Today, Feedonomics synthesizes and transforms more than 1 trillion product listings every month, giving us unique insight into how product information is structured, enriched, and optimized across the global commerce ecosystem. We believe that scale positions us to play an increasingly important role as AI-driven discovery and agentic commerce continue to evolve.
Over at e-commerce specialists, President Harley Finkelstein offers no argument against the idea that there are “early structural changes” going on in the market, but qualifies that view:
Let’s look at the type of merchants benefiting from these AI shifts. Early indications show that AI search has been particularly helpful to some of the smaller brands that form the long tail of commerce. These are brands that also happen to make up the majority of Shopify’s merchant base, smaller businesses with specialized products built for a particular customer. We saw that AI search was starting to dis-proportionately benefit the long tail in 2025. And that trend has continued, with 75% of AI-attributed orders coming from outside our top 100 categories.
The explanation for this is simple, he contends:
While search engines rank by popularity against a handful of keywords, AI agents make multiple calls into Shopify’s Catalog working with richer structured data to match products with the buyer’s specific intent rather than just keywords. So when a buyer asks an AI assistant for the best car seat that fits three across the Sedan, traditional search focuses on the keywords ‘car seat’. An agent, however, understands the actual need, the dimensions, the vehicle type, and the fact that they need [to fit] three. It searches across all of those constraints at once to find the product that actually works not just the one that ranks highest.
That level of precision is vital, he says:
In this world, relevancy reigns. So, specific products made for a specific buyer do particularly well. Same for things like reef-safe sunscreen that doesn’t leave a white cast or even the best dog harness for a French bulldog. These are real Shopify products that have benefited from the specificity of AI search in the last quarter, and this specificity is leading to better conversion for merchants.
From the buy side, the Shopify shopping journey is being compressed as half of all AI-referred sessions land directly on a product description page, 2.5x more than with traditional search. That provides a serious tailwind for growth, argues Finkelstein, but one that has had to be worked for:
Our Catalog you can think of as the authoritativets and best brands. For nearly two years, we’ve been investing in the search index, ensuring over 1 billion products and 20 years of commerce experience is distilled for agents. It structures merchants product data, so every and any AI partner can access it directly, giving agents the ability to discover, understand and recommend our merchants’ products
It’s been worth the spadework, he insists, as Catalog will be one of Shopify’s most important assets for years to come:
We’re seeing that AI searches powered by Catalog converted twice the rate of those using scraped data. That is because with Catalog, merchants’ products show up complete, accurate, and with the right context when someone is ready to buy. Put simply, Catalog is the discovery engine for the future and Shopify built it and owns it.
Conversion from our Catalog being 2x more than the general AI search is pretty remarkable. But the thing that on a very personal level, and I think at Shopify level, we’re really excited about is that this is real. I’ll tell you a quick example. We were looking for a screen-less phone for our daughter, for our 10-year-old, and I just started putting in my own prompt to look for different products. Five years ago, I would’ve done that in search, and I probably would have received some big box retailer selling a bunch of different random products. Instead, I was directed to the Tin Can Phone, which is this amazing product, a Shopify merchant. The product’s amazing. I never would’ve found it otherwise.
My take
A revolution no doubt, but as even the most fervent of AI evangelists are careful to caveat, one that’s still in its very early innings with everyone staking leadership claims and trying to work out which standards horse to back. It will take time for all this to calm down into a consensual clarity of vision. Until then, caveat emptor remains as true as it ever was.
