AI-led checkout is starting to move from theory into real trading conversations.
For established Shopify brands, the interest is easy to understand. Performance channels are harder to scale, customer acquisition costs remain high, and anything that promises to shorten the path from discovery to purchase deserves attention.
At the same time, margins are tighter, teams are leaner, and platform costs add up quickly. That makes it important to look past the headline and understand how this type of channel actually behaves in practice.
The real question most brands are asking is not “does this work?”, but “does this work for us, without undermining what we already have?”
Why this is coming up now
Most DTC brands are operating under familiar pressures:
- paid media is less predictable and more expensive
- organic growth takes time to compound
- internal teams are stretched
The initial rollout is US-only, with wider availability expected to follow, which is why this is already coming up in planning conversations.
Against that backdrop, platforms are looking to reduce friction by collapsing discovery, comparison and checkout into a single experience.
That is the context for AI checkout initiatives emerging from partnerships between platforms like Shopify and OpenAI.
The promise is simple: help customers find what they want and buy it faster.
The detail is where it gets more interesting.
What AI checkout actually means in practice
AI checkout allows customers to discover products and complete a purchase directly within an AI interface, rather than visiting a brand’s storefront.
From a merchant perspective, several things stay the same:
- you remain the merchant of record
- fulfilment, tax, returns and customer service are unchanged
- Shopify still handles the underlying commerce infrastructure
Where it differs is commercially.
If a sale completes via the AI checkout interface, the merchant pays an additional success fee, on top of normal Shopify and payment processing fees.
This is not a replacement for your checkout or marketing stack. It is a new acquisition and conversion channel, with its own economics.
The real commercial question: cost versus control
Most early discussion has focused on the size of the fee. In practice, the more important issue is control.
With paid search, paid social or affiliates, brands can:
- control budgets
- choose which products to promote
- test and optimise performance
- scale or pause activity deliberately
AI checkout works differently.
Product visibility and recommendations are handled by the platform. The cost is fixed. Optimisation options are limited. Attribution is less transparent than most commerce teams are used to.
That does not make it a bad channel. It does mean it behaves very differently from the channels brands already know how to manage.
This is why paid media remains a core channel for most brands.
Where the real risk and opportunity sit
For established brands, AI checkout can unlock genuinely incremental demand in the right scenarios. It can surface products to customers who may not have discovered the brand through traditional search, paid media or owned channels.
The challenge is separating that upside from sales that would have happened anyway.
The key question is not: “Will this drive orders?”
It is: “Would these customers have bought from us regardless?”
If AI checkout mainly captures demand that would have converted through SEO, CRM, paid media or returning customers, the brand is paying an extra fee for the same sale. Over time, that quietly erodes margin.
There is also a competitive consideration. As AI-led checkout becomes more common, brands that are not present may find competitors surfaced more prominently simply because they offer a faster path to purchase. In that scenario, participation may be less about growth and more about avoiding avoidable loss.
On the other hand, where the channel introduces new customers or unlocks demand that existing channels are not reaching, the economics can make sense, even with an additional success fee.
For established brands operating at scale, even small percentage shifts become meaningful as volume grows. That is why finance and commercial teams tend to be cautious by default and why this channel benefits from clear guardrails and disciplined evaluation.
A simple margin-impact example
Where this becomes commercially significant is when volume increases.
To make this tangible, it helps to look at simplified examples from categories we work with regularly.
Beauty brands
- £65 average order value
- around 70 percent gross margin
On a typical £65 order, gross margin is roughly £45.50 before marketing.
A 4 percent AI checkout fee equates to £2.60 per order, reducing gross margin by around 5-6 percent.
On a small number of genuinely incremental orders, that may be acceptable. If 10-15 percent of total order volume starts flowing through this channel, the cumulative impact becomes material very quickly.
Supplements and nutrition brands
- £55 average order value
- around 55 percent gross margin
That leaves roughly £30.25 gross margin per order before marketing.
A 4 percent fee is £2.20 per order, reducing gross margin by 7-8 percent.
In categories where repeat purchase, subscriptions and contribution margin matter, that reduction is not trivial. The channel only works if orders are clearly incremental or lifetime value offsets the upfront hit.
Where AI checkout could make sense to test
This is not something to dismiss outright, nor something to adopt by default.
A controlled test can make sense when:
- margins comfortably absorb additional channel costs
- products rely on discovery rather than strong brand intent
- the brand is comfortable experimenting with clear guardrails
In practice, that usually means:
- limiting access to high-margin or long-tail SKUs
- excluding hero products that already convert well
- setting a defined review period rather than letting volume grow unchecked
In those cases, AI checkout behaves more like a marketplace-style pilot than a core growth lever.
What tends to matter most in practice
The most common mistake is treating this like a performance channel.
It is not something you can bid on, tune aggressively, or optimise week to week. The value comes from access to demand, not control over mechanics.
Brands that succeed with it tend to:
- be selective about where it applies
- measure incrementality carefully
- stay disciplined about margin impact
As new channels emerge, the importance of optimising the ones you can control increases, not decreases.
Our view
AI checkout is real, optional and commercially meaningful. It is not something to ignore, and not something to rush into.
For most established Shopify brands, the right approach is calm evaluation rather than immediate adoption. Test where it makes sense. Measure properly. Protect margin.
Features will keep changing. The brands that win are the ones that make decisions that still look sensible six months later.