By Lance Allison, Founder of Ruby Digital Agency | July 2026 | ~5 min read
This past year, every migration company said the exact same thing: “AI will change the way you work.” For most of them, that means using an AI chatbot to write product descriptions. What we actually wanted was a straight answer to a sharper question — can an AI agent really run a Shopify Plus migration from start to finish? Not just assist with it. Run it.
So on a recent BigCommerce to Shopify Plus project, we handed the lion’s share of the work to one. Here is exactly what happened, along with the numbers.
In This Article
- What an AI-Run Migration Actually Means
- What the AI Got Right
- Where a Human Stayed in Charge
- The Results, in Numbers
- What This Means for Your Migration
What an AI-Run Migration Actually Means
Let me clarify something before I go further. We didn’t just tell a chatbot to migrate “my store” and walk away. The AI agent — Claude, running our own migration scripts — took in the client’s raw platform exports, mapped every product, variant, customer, and order to its equivalent in Shopify’s schema, and sent each record through the Admin API. A human set the strategy and signed off at every checkpoint. The agent handled the thousands of monotonous, error-prone steps that normally swallow most of a developer’s week.
The source data was five CSV exports — no expensive third-party connector, no API scraping. Those flat files held everything we needed, right down to the per-parcel tracking numbers that tools like Cart2Cart quietly leave behind.
What the AI Got Right
Three things stood out, and the first was how the agent handled edge cases. BigCommerce happily lets you stack duplicate variant combinations, so one product had quietly bloated to 184 variants when only 66 of them were ever real — the other 118 were stale duplicates that Shopify, which enforces unique variants, would have rejected outright along with the entire product. Rather than choke on it, the agent recognized the collision, pared the list back to the correct 66, and carried on. Try reconciling that by hand across a few thousand SKUs and you will miss it more often than not.
Order history was the second, and it is where most migrations quietly cut corners. We backdated thousands of orders to the dates they were actually placed, held onto the original order numbers, and stitched every shipment’s tracking number back onto the right line items — including the split shipments that referenced a parent order rather than the child — so a returning customer sees the history they remember instead of an empty page.
The third was safety, which is the thing that genuinely keeps me up at night on a migration this size. Every historical order was imported with receipts suppressed, customer notifications suppressed, and inventory deliberately bypassed, because missing any one of those flags means you either email your entire customer base by accident or quietly corrupt live stock. A person doing this by hand is careful at order fifty and sloppy by order four thousand; the agent applied the same settings, correctly, on every single call.
Where a Human Stayed in Charge
Here is the part the AI hype tends to skip: none of this replaced judgment. We still pulled a sample of twenty records from each type and went looking for trouble on purpose — guest checkouts, refunds, foreign-currency orders, that 184-variant monster — and got the client to sign off before anything scaled to the full catalog. We double-checked the weight unit before trusting a single shipping rate. And we walked straight into Shopify’s order-creation rate limit, which on a development store slows you to roughly five orders a minute, so the agent had to pace itself and back off when it got throttled. You only really learn that limit once it bites you.
Then we checked the work. Every value was queried back out of Shopify and compared against the source, down to the cent. The speed came from the agent; the trust came from verifying.
The Results, in Numbers
| Metric | Outcome |
|---|---|
| Source data | 5 BigCommerce CSV exports (no paid connector) |
| Products & variants | Full catalog migrated; one 184-variant product deduped to 66 |
| Orders | Thousands, backdated to their original dates |
| Tracking numbers | Preserved per parcel, split shipments included |
| Data accuracy | Verified against source down to the cent |
| Safety flags | Receipts & notifications off; inventory bypassed on every call |
The honest headline is not that AI did the whole thing on its own. It is that a job which normally burns through weeks of developer hours ran on a small fraction of them, with fewer mistakes, because the tedious ninety percent was automated and the human ten percent went to strategy and checking instead of copy-paste.
What This Means for Your Migration
If you are planning a move to Shopify or Shopify Plus, this changes the math. The real risk in a migration was never the strategy — it was the thousands of tiny, forgettable manual steps where fatigue quietly loses data. Hand those to an agent that never tires, keep an experienced human on strategy and verification, and you get a cleaner cutover in less time and for less money.
That is how we run migrations at Ruby Digital Agency now. AI is not coming for the migration itself — it is coming for the tedious, breakable middle, and that is good news for any brand whose revenue depends on getting the move right.
Thinking About Migrating to Shopify Plus?
We plan the strategy, run the heavy lifting with AI, and verify every record against your source data before go-live. Book a migration strategy call and we’ll map your move.
Related Reading
- Shopify Store Migration Services
- Shopify Plus Implementation & Consulting
- 10 Reasons to Migrate from BigCommerce to Shopify
- More Shopify Guides on Our Blog
Lance Allison
Founder & CEO, Ruby Digital Agency
Lance Allison is a Shopify Select Partner and eCommerce migration specialist based in Salt Lake City, Utah. He has helped hundreds of merchants move to Shopify and Shopify Plus, and specializes in complex, data-heavy platform migrations.
