How-to
A six-step method to move one store process from manual work to a live automated one, from order-status questions to returns.
Updated 6 min read
The short answer
To use AI in ecommerce, pick one store process, such as order-status questions, product content or returns. Connect your store data, set rules and approvals, test on real orders, then measure the result before adding a second process.
Key points
Step by step
Each step builds on the last. Skip none of them.
Choose a repetitive job: order-status questions, product descriptions or return requests.
Count the hours and the volume for that process, so you can prove the change later.
Link orders, products and customer records so the system works from the facts.
Write what it may do alone, such as answer status questions, and what a person approves.
Run past and live orders through it and fix every wrong answer before launch.
Compare hours, speed and errors against the baseline, then pick the next process.
Retail adoption
89% use AI or are assessing projects
Cost impact
94% say AI cut operating costs
Shopper traffic
AI-sourced visits grew 1,300 percent
Adoption is already mainstream. Retail and consumer goods firms are moving: in NVIDIA's survey, 89% use or assess AI and 94% say it cut annual operating costs.
Shoppers are moving too. Generative AI sources sent 1,300 percent more traffic to US retail sites in the 2024 holidays than a year earlier, Adobe reported.
Order questions
Status, delivery and tracking replies
Product content
Descriptions drafted from your catalog
Returns
Requests sorted and routed by rule
Marketing
Follow-ups sent on triggers
The most useful AI applications in ecommerce sit in repeated, rules-based work, which is where using AI for ecommerce, and any AI ecommerce business, should start.
Order-status replies, product content and return handling all follow clear patterns.
Gen AI for ecommerce suits writing and reading tasks, such as drafting descriptions or sorting customer messages.
Classic workflow automation in ecommerce, or ecommerce business process automation, suits fixed steps, such as updating an order when it ships. Our ecommerce automation page shows how this looks for an automation ecommerce brand.
Weak first choice
Strong first choice
Returns are a strong candidate: NRF and Happy Returns expect 19.3% of 2025 online sales to come back, and 64% of merchants rank fixing returns as a priority.
Cart abandonment is another. Baymard puts the average documented rate at 70.22%, with extra costs the main cause. Pick the process where volume and pain are highest, then check the data you hold for it.
Answered without a manual lookup
A working setup reads events from your store and acts on them. Shopify documents its Flow tool this way: it monitors the store for events and runs a chosen sequence of actions in response.
AI adds the reading and writing on top of those events.
This is where ai ml in ecommerce becomes practical, with a model classifying a message or drafting a reply while fixed rules move the order along.
Runs on its own
A person approves
Give any ecommerce process automation narrow permissions at first. Let it answer status questions alone, and have a person approve refunds, exceptions and anything that touches money.
The rules apply to AI as much as to people. The FTC has made clear that AI gets no exemption from existing law, and its fake-review ban covers AI-written reviews.
Its mail and internet order rule also requires shipping within the promised time or the buyer's consent to a delay.
Common mistakes
Safer approach
The first mistake is automating everything at once. A narrow start gives clean results and clear lessons.
Our AI in e-commerce examples show which tasks repeat most, and the guide to AI for ecommerce brands covers the wider picture.
The second is skipping the baseline. Without hours and error counts from before, you cannot show what changed.
Teams also forget that shoppers still want choice: in Walmart's research, 46% said they were unlikely to let an assistant handle a whole shopping trip.
Our data
We asked ChatGPT, Gemini and Perplexity 10 buyer questions about AI for e-commerce brands. They named 130 companies, and 82% appeared in only one of the three.
| Criterion | ChatGPT | Gemini | Perplexity |
|---|---|---|---|
| Companies named | 45 | 52 | 64 |
| Sites cited most | shopify.com (5 of 10) | vellum.ai (4 of 10) | pearllemonai.com and aiagencyradar.com (2 of 10) |
Nexum measurement, October 20, 2026, via DataForSEO: 10 buyer questions to each AI, US English, 30 answers in total. 7 companies appeared in all three. Google showed an AI Overview for 8 of the 10 questions.
FAQ
Final step
You leave knowing which processes to automate first and what each one costs you today, whether we work together or not.
You can keep paying for manual work, or find out this week exactly what it costs you.
What happens on the call
Before
You answer 3 quick questions when you book, so we come prepared.
On the call
We find the manual work that costs you most and put a number on it, live.
Decide
An honest read on whether we're the right fit. If we're not, you'll hear it on the call.
Once you book, we look at your site and tools before the call, so the 30 minutes go to your numbers, not introductions.
Prefer to write first? Email us directly: contact@nexumautomations.com
