I'm not particularly an "AI will fix everything" person - but if you follow any AI news it's becoming increasingly clear that the largest technology platforms are pushing hard to turn AI into a place where shopping happens right in their apps, not just where people go to research or 'chat'.
And so if you're responsible for growth, revenue, or digital performance across your online store, then AI-driven shopping is an important topic in 2026, because when buying behaviour changes, the rules for visibility change with it.
In this article, we'll look at future predictions on how AI-driven shopping is starting to take shape, why accessibility is set to matter far beyond compliance, and how to make sure your products remain visible as buying behaviour continues to evolve.
The shift towards AI-driven shopping that's already underway
Over the past year, we've seen a clear pattern emerge: AI systems are moving beyond recommendations and into execution.
This idea is often called agentic commerce, which simply means AI completing tasks on someone's behalf. Not just "show me the options", but "compare these, pick the best one, and buy it".
Google, Shopify, Microsoft, OpenAI, and Amazon are all experimenting with versions of this. Google and Shopify recently announced the Universal Commerce Protocol (UCP) - an open standard designed to let AI agents interact with your own online store and the products you're selling across the entire shopping journey, from discovery through to checkout and post-purchase support.
The important thing to note here isn't predicting the exact interface your customers will use in five years' time. It's recognising that AI is becoming a new sales channel, just like search engines and marketplaces did before it.
And early adopters almost always win.
The accessibility win hiding in plain sight
There's an important human dimension to this.
Many disabled people are already using AI tools every day to help their daily life. People who rely on keyboards, voice input, screen readers, or other assistive technologies. AI can explain in plain English, summarise complexity, and bypass frustrating interfaces.
So it's not a stretch to imagine the same pattern applying to shopping.
Why would anyone manually visit 20 different websites - many of which are slow, confusing, or inaccessible - when you can ask an AI for recommendations and buy from there? And for a lot of shoppers, that would be a genuine improvement.
That shift alone is likely to make online shopping more inclusive. And that's a good thing.
But it also introduces a competitive reality:
AI agents can only recommend and sell products from stores they can reliably understand.
If you weren't already convinced that an accessible site is beneficial for your customers, then this is where accessibility stops being a nice-to-have and starts becoming commercially important.
Amazon has already been testing this - and it shows the risk
Amazon's recent “Buy For Me” experiment is a useful early signal - and the reaction from independent merchants shows what can go horribly wrong when agents act without enough certainty.
A recent to report in the Financial Times explained how independent retailers discovered their products being listed and sold through Amazon's AI-driven experience without consent, sometimes with incorrect information or stock availability. Modern Retail also reported that merchants were unhappy with how Amazon positioned itself between them and their customers, including the use of Amazon-controlled relay email addresses that interfered with customer data and communication.
You can make moral arguments about this, but there's also a practical one: if an agent can't reliably use your site, someone else will try to "standardise" the experience for you.
While it's not entirely clear what went wrong with some of these stores, when a platform cannot reliably understand or transact on a merchant's site, it has an incentive to proxy the experience, standardise it, and pull it into its own system.
That standardisation often strips out nuance, brand control, and direct customer relationships.
The mere existence of opt-out mechanisms tells us something important: merchants are going to care, increasingly, about how AI agents interact with their stores - and on what terms.
Where AI shopping agents commonly fail on product pages
Here's the reassuring part if you already care about customer experience.
AI agents fail in many of the same places humans fail.
On product pages, the most common problem areas seem to be product variants that change visually but not programmatically, stock messages that aren't clearly exposed, price changes that only appear after interaction, add-to-cart actions with no clear success or failure signal, and errors communicated only through colour, animation, or layout.
Without a deterministic confirmation or error state, agents cannot know whether the action succeeded, whether retry logic is needed, or whether the flow should continue to checkout.
These are exactly the kinds of issues that frustrate customers who browse without a mouse, rely on keyboards, or use assistive technologies.
Humans can adapt. But AI agents often don't. They skip, hallucinate or produce unreliable results.
What decides whether your products get shown by AI agents
As AI becomes a sales channel, the primary optimisation goal shifts.
It's no longer just about relevance or brand recognition. It's about certainty.
AI agents are optimised for clear product identity, predictable interactions, and reliable outcomes. If a product page introduces ambiguity, the safest option for an agent is simply not to recommend it.
That's why I expect we'll start hearing terms like “eligible listings”, “supported checkout”, “reliable integrations”, or “agent compatible”. These won't be framed as accessibility requirements. They'll be framed as platform quality standards.
But under the hood, these map very closely to the same foundational patterns accessibility specialists have been fixing for years.
Why?
Because accessibility is the cheapest way to make complex interfaces machine-readable at scale.
Why accessibility helps AI agents understand your store
When business owners hear about "accessibility", they often think about compliance and regulations.
That's not the useful mental model here.
Accessibility, at its core, is about making sure names are explicit, roles are clear, values and states are exposed, and errors explain what happened and what to do next.
Those qualities make interfaces easier for humans with access needs. They also make interfaces easier for machines to reason about.
That's why I expect AI commerce systems to treat accessibility implicitly as a quality signal, alongside things like data consistency, fulfilment reliability, returns behaviour, and customer satisfaction.
Not because AI systems particularly care about ethics - but because accessible systems are easier to automate, test, and scale.
A note on commerce standards and AI protocols
You may have seen recent announcements from Google and Shopify about the Universal Commerce Protocol (UCP) proposal.
While it's not confirmed as a standard yet, UCP is an open standard designed to give AI agents a shared language for commerce - covering discovery, buying, and post-purchase support - and to work across platforms and alongside other protocols like Agent2Agent (A2A), Agent Payments Protocol (AP2), and Model Context Protocol (MCP).
It's an important signal that the ecosystem is aligning around the need for structured, reliable commerce interactions.
But you don't need to bet on UCP "winning", or even on which platform ends up dominating AI-driven shopping.
Improving accessibility on your product pages makes your store easier to understand for any agent, on any surface, using any protocol.
The questions your product pages must answer
If AI is becoming a new sales channel, here's the simplest way I'd assess the readiness of your products - and it's something you can sanity-check yourself without new tools, new vendors, or a six-month project.
Can your product pages clearly answer these questions - for someone who isn't using a mouse, and for a system that can't "see" your design - without guesswork?
- What exactly is this product?
- What options or variants can I choose?
- What changed when I selected that option?
- Is it in stock right now?
- What happens when I add it to cart?
- Did that action succeed or fail?
- If it failed, what do I do next?
This often breaks down when key choices only appear after a mouse click, or when product options are built in a way that assumes visual interaction. If the product doesn't fully exist without clicking around, the options are effectively hidden, and both keyboard users and AI agents are forced to guess, or to give up.
If the answers rely on visuals alone, animations, or assumptions about how someone is browsing, both customers and AI agents will struggle.
If the answers are explicit, predictable, and exposed in the page itself, you've removed a whole category of friction - for people and for machines.
I regularly see these failures in areas like product options and variant selectors, as shown in my review of accessible product options and my breakdown of accessible custom dropdowns. It's also why I've written before about how Shopify checkout accessibility is largely solved, while product pages remain the fragile part of the flow in this article on checkout vs product pages.
Being easy to understand is how your store stays visible as AI shopping grows
AI shopping isn't a distant prediction anymore. It's the clear direction of travel.
The stores that win won't be the loudest or the most experimental. They'll be the easiest to understand - for people and for machines.
If your store works well for customers who browse without a mouse, use a keyboard, or rely on assistive technologies, it's also far more likely to work well for AI agents deciding what to recommend and what to skip.
That's not a compliance argument.
It's a commercial one.
Early adopters get the head start. Start by making your product pages unambiguous, then keep iterating as the channel matures.
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