Draft three product descriptions with the built-in generator, edit them to your voice, and time the loop — that is your baseline cost per SKU.
Check your plan's current AI features in the admin rather than a blog post (including ours) — Shopify plan-gates and iterates monthly.
List the workflows that cross systems: store + helpdesk + email. Native features stop at the platform edge; that boundary is where implementation work starts.
Ask what you would measure. If the answer is "vibes," no tool — native or hired — will show you whether it worked.
Where the native path runs out
Scale breaks the one-at-a-time model: a 900-SKU catalog needs generation grounded in structured product data, a review queue, and voice consistency that per-product prompting cannot hold. Cross-system workflows break it too — support drafting needs order context, lifecycle copy needs segment logic, and none of that lives inside a single admin. And measurement breaks it last: platform-reported wins need reconciling against your actual P&L. Those three boundaries are our service list, which is not a coincidence.
Shopify AI questions
What AI is built into Shopify?
Shopify ships its AI under the Shopify Magic umbrella (with Sidekick as the assistant) — product-description drafting, text generation in the editor, and assistant-style help are the headline features on Shopify's own marketing. We deliberately do not enumerate a full current feature list here: Shopify iterates fast and plan-gates features, so the accurate answer lives in your own admin. The useful question is not "what exists" but "what does mine already do" — check before buying anything third-party, including us.
Is Shopify Magic good enough for product descriptions?
For a small catalog with a human editing each output — often yes, and you should use it before hiring anyone. Where it runs out: hundreds of SKUs needing consistent voice and structured attributes, multilingual catalogs, and grounding in data beyond the product form. That gap between one-at-a-time drafting and a reviewed pipeline is precisely where our catalog service sits, which is why this guide tells you to try the native path first.
What should I never let AI do in my store unreviewed?
Publish product claims (materials, sizing, compatibility — wrong ones are refunds and legal exposure), talk to angry customers, issue refunds or make policy exceptions, and generate reviews or urgency mechanics in any form. The review gate is not AI skepticism; it is the difference between automation and abdication.