AI Agents for Ecommerce: Which Workflow to Hand Over

Adopting AI is not one decision. It is a series of small ones, and they all come down to the same question: which of the things your team does by hand is a real fit for an agent, and which is not. Most stores never get that far. Either AI becomes a project with a steering group and no owner, or someone bolts a chat box onto the storefront and calls it done. Neither one teaches you anything about your own operation. The useful move is narrower. Look at the work your team repeats every week, work out which of it an agent can own, and hand that part over. This covers how to tell the difference, with returns, promotions, and referrals worked through as examples.

Custom Agents

Bring the workflow you still do by hand.

Book 30 minutes, tell us the task your team repeats every week, and we will tell you straight whether an agent can own it.

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What makes a workflow worth handing over

Every team has a memory of software that was going to save time and did not. So the thing to judge is not how impressive the automation sounds. It is whether the work is repetitive enough that people feel the relief quickly, and whether the output is checkable enough that they come to trust it. Relief and checkability are what separate a workflow an agent can own from one that quietly gets abandoned. The three examples further down are custom teammates, built around a workflow rather than picked off a shelf. They are worth reading even if none of them is yours, because the reasoning transfers.

Five questions before you hand a workflow over

Run your candidate through these before you commit to it:

• Does the data already exist somewhere readable, rather than in someone's head or a supplier's inbox
• Does the decision come round on a schedule, weekly or daily, rather than twice a year
• Can someone on your team write down how a good decision gets made today, even roughly
• Is there a person who reviews the output before anything happens
• If it gets one wrong, is that cheap to undo

A workflow that answers yes to all five can usually be running inside a week. One that fails on where the data lives is a data project wearing an AI costume, and the plumbing needs sorting before an agent is worth discussing.

Worked example: returns

Returns are the clearest fit of the three, because the cost is obvious and the data is already sitting in your store. The manual version is a spreadsheet someone builds at month end, if they build it at all. What came back, which products, which reasons, and what it cost once you count the refund and the handling. A returns teammate reads that continuously instead. Which products come back most, which variants and sizes drive it, which reasons keep repeating, and what your return rate is doing over time. You see the pattern early enough to act on it, whether that means a sizing note on the product page, a supplier conversation, or dropping a variant that never gets kept.

The decision stays with you. The agent tells you one colourway accounts for most of the returns in a line. Pulling it is your call.

Worked example: promotions and discounts

Most stores run more promotions than they review. Codes go out, revenue moves, and nobody goes back to work out what the discount actually cost. A promotions teammate watches discount performance against your order data. Which codes are getting used, what they did to volume, and what was left of your margin once they were applied. When a promo is giving away more than it is bringing in, you hear about it while it is still running rather than in a post mortem three weeks later.

It flags and it recommends. Changing a price or ending a campaign is still something you do.

Worked example: referrals and affiliates

This one has a prerequisite the other two do not, and it is worth being straight about. Referral and affiliate data usually lives in a separate app rather than in Shopify, so it has to be connected before an agent can say anything useful about it. That is a custom integration, which is included from the Growth plan onwards. Once it is joined to your order data the questions get interesting. Which referrers send customers who keep what they buy rather than return it, which ones send people who order once and never come back, and what a referred customer is worth next to the commission you pay for them.

What building one actually looks like

You do not specify an agent. You describe the job. The Insights and Inventory teammates come as standard, so most stores begin there and get used to asking questions of their own data. When the workflow you care about sits outside that, we build a custom teammate around it, usually within a week of you asking, along with the integrations it needs to see the data.

Where to start this week

Four steps, and none of them need a budget approved:

• Write down the three tasks your team repeats every week that nobody enjoys
• Run each one through the five questions above and keep whichever answers yes the most
• Check where that data lives, and whether it is in Shopify or somewhere that needs connecting
• Start with answers rather than actions, and check a few against your admin before you build anything on top

None of this needs to be a programme. Hand over the workflow with the clearest answers, then judge it on whether your team still wants it a month later.