When Generative AI Meets Cross-Border E-Commerce: What Should China's SMEs Do?

A while back, I had dinner with a few friends who run cross-border e-commerce (跨境电商) businesses. A few drinks in, one of them suddenly asked me:

"You know, I've got a dozen-plus people at my company — loading up product listings, writing product detail pages, shooting short videos, every day. The last couple of years a whole pile of AI tools have shown up: ChatGPT, Midjourney, plus the assistants the platforms themselves have built. Should I get on board or not? If I do, I'm scared of stepping into a trap; if I don't, I'm scared of getting left behind."

I didn't rush to answer.

Because I realized this isn't just his confusion alone. It's a question that more than 120,000 Chinese cross-border e-commerce companies and over a million practitioners have collectively run into over the past two years.

Generative AI has arrived, and Chinese cross-border e-commerce is standing at a watershed.

First, a Fact: Cross-Border E-Commerce Has Quietly Grown Tenfold

What does "watershed" mean?

It means that while people are still debating "should I get into cross-border e-commerce," the size of this industry has already grown beyond what you'd imagine.

Let me show you a few numbers.

Over the past five years, the trade volume of China's cross-border e-commerce has grown tenfold. In 2023, total import and export hit RMB 2.38 trillion, up 15.6% year-on-year. Of that, exports reached RMB 1.83 trillion, up nearly 20%.

What does that mean in practice?

There are now more than 120,000 cross-border e-commerce companies nationwide, over 200,000 standalone stores (独立站 — DTC storefronts independent of marketplaces like Amazon), more than 1,000 cross-border e-commerce industrial parks, and more than 2,500 overseas warehouses (海外仓) with combined floor area exceeding 30 million square meters. The government has approved 165 cross-border e-commerce comprehensive pilot zones (综合试验区, a Chinese government-designated testing zone for cross-border e-commerce policy) in one go.

Some predict that by 2025, the B2B cross-border e-commerce market will surge to RMB 13.9 trillion.

Can you still call this "small business"?

Here's the thing that hits harder: this crowd of sellers is no longer just staring at the big platforms like Amazon and Alibaba.com. Standalone stores have quietly emerged — in 2024 the standalone-store market reached RMB 3.4 trillion, accounting for 35% of the entire B2C market. One brand that started out making power banks saw its standalone-store revenue growth hit 71.75% in 2022.

While everyone else is still fighting for platform traffic, it has turned itself into a traffic gateway.

Live commerce (直播带货) has crashed the party too. Short-video apps have been the world's most-downloaded category since 2020, and cross-border live commerce has become a fresh breakout. Sellers used to trudge from trade show to trade show winning customers one at a time; now a single livestream session can close a whole wave.

Next Thing to Know: Generative AI Is Arriving Faster Than You Think

Cross-border e-commerce is growing hard, and generative AI is arriving even harder.

What is generative AI, anyway?

Plainly put, it's the kind of AI where you give it one line and it can generate a paragraph of text, an image, a video, or even a line of code. ChatGPT is one; those image-drawing tools are another; and so is Rufus, Amazon's conversational shopping assistant.

It's different from the old-school AI that "only classifies, only predicts." This one creates.

And in China, the pace is a little frightening.

AIGC (AI-Generated Content) apps have surpassed 73.8 million users, up eightfold year-on-year. Experts predict that by 2035, the economic value generative AI creates globally will approach RMB 90 trillion, with China capturing more than RMB 30 trillion — over 40% of the total.

The government has been rushing to lay the track too. In August 2023, the Interim Measures for the Management of Generative AI Services officially took effect — encouraging innovation on one hand while setting rules with the other. By April 2024, 117 domestic large language models (大模型, LLMs) had completed service filing (服务备案 — regulatory registration).

This isn't the future. This has already happened.

So, What Is AI Actually Doing in Cross-Border E-Commerce?

Let me break it down for you.

Right now, AI in cross-border e-commerce is mainly doing three things: personalized recommendation, insight mining, and content creation.

Sounds abstract? Let me give you a few examples.

There's a sales rep who used to agonize for ages over a single cold outreach email (开发信) to a new prospect. Now he just drops the company name and product name into the tool, tweaks the wording a bit, and a high-quality prospecting email rolls out with one click.

Amazon launched an AI shopping assistant called Rufus. When an overseas buyer asks "is this one good for camping?" or "how does this compare to that one?", Rufus can make recommendations and lay out comparisons based on the chat.

One international marketplace rolled out an "AI business assistant" — the moment a buyer posts a request, it understands instantly, auto-generates suggested replies, and even fills out the quotation for you.

Building product detail pages, producing product images, writing livestream scripts, forecasting inventory… AI has wormed its way into every corner of cross-border e-commerce.

On Alibaba.com alone, more than 100 million product listings have been generated by AI. Merchants now have more than 40 scenarios where they can put AI to work.

Think about it — when a tool can take half the workload off your copywriter, your designer, and your customer service team, can you really afford not to use it?

But Hold On — Don't Rush In.

After talking it through with those friends, I noticed something interesting.

Everyone says AI is great, but the ones actually using it smoothly? Very few. I've summed up four pitfalls that almost every SME has stumbled into.

Pitfall one: everything AI writes looks the same.

It makes sense when you think about it. One company lists the same product across several platforms at once and needs several versions of copy. But everyone's using roughly the same AI models, feeding roughly the same data — and some people even just use a single tool.

The result? The same product's description on Amazon, on the standalone store, and in the livestream looks like it came out of the same mold.

Consumers find it fresh the first time, and get annoyed by the third. Brand recognizability vanishes, and loyalty goes down with it.

Homogenization is the same gift AI hands to every lazy person.

Pitfall two: not enough people, and not enough skills.

AI tools are multiplying to the point where new ones pop up every month, with feature updates coming as fast as phone OS upgrades.

SMEs were already short on cross-border e-commerce talent, and now they have to chase AI learning on top of it. Worse, many bosses are themselves unsure about AI — they don't know which one to pick or how to integrate it with the business. The upshot: employees have no one to lead them, no one teaches the tools, and everyone's groping in the dark.

Pitfall three: AI sounds utterly convincing, but whether it's actually right — you have no way to tell.

AI has a habit. It doesn't guarantee what it says is correct; it can confidently fabricate nonsense.

But here's the thing: SMEs already lack the data and case studies to verify whether AI's marketing advice actually works. Verification costs money, time, and headcount, and cross-border e-commerce sales costs are already high — nobody wants to fork out extra for "trial and error."

What usually happens is that mid- and junior-level staff use it the most eagerly, but they're also the least equipped to judge the quality of AI's output. The people using it and the people who can judge it are not the same crowd.

Pitfall four: toss your data into AI, and your crown jewels may leak out.

For convenience, employees toss customer purchase records, new product specs, even marketing strategies into AI tools for analysis. There are over 100 domestic large language models on the market, and the same person might use one model today and another tomorrow.

Once sensitive information slips into a competitor's hands, your product designs, customer lists, and pricing strategy are laid completely bare.

You treat AI as a helper; AI can just as easily work as a mover, carrying your crown jewels out the door.

So, What Should SMEs Do?

I told those friends: don't panic. The pitfalls are real, but so is the path.

Drawing on what I saw in them, plus my own thinking, I've boiled it down to five points.

Point one: squeeze every drop out of the free stuff before you talk about going advanced.

When resources are tight, don't start by throwing money at paid tools. Platforms like Amazon and Alibaba.com offer their own AI tools and companion online courses, and a lot of them are free. If you've never touched AI, start there.

For paid tools that employees buy out of their own pockets, reimburse them within a reasonable range to encourage learning. Platform-run skill competitions and industry meetups — attend them if you can. You can also partner with universities and use their training software to run marketing sandbox simulations — you get to practice without actually burning your marketing budget.

For learning, if a free venue can solve it, don't walk into a paid casino.

Point two: don't fully trust AI — build a verification mechanism.

AI-generated content needs a human gatekeeper. How do you gatekeep it?

One, use big data. Cross-border e-commerce platforms themselves hold a vast sea of consumer data. You can first use big data to mine consumers' real habits and preferences, then let AI generate content based on those insights, and finally use data feedback to verify the results.

Two, lean on your buyers. Whichever country your goods are sold into, go ask partners in that country how this version of marketing content reads to them. Frontline feedback beats guessing by gut feel.

Three, run sandbox drills. University training bases and livestream bases can all be used for practice. Test first in a safe environment, then take it out for real.

Point three: find partners and team up — don't go it alone.

Cross-border e-commerce isn't something one person can shoulder alone. Platforms, technology vendors, peer companies — any of them can be your partners.

Build strategic partnerships to share resources, technology, and experience. There are plenty of people in industry communities studying "how exactly to use AI in cross-border marketing," and that hard-won experience is worth mining.

The government is pushing public training-data resource platforms, and companies should actively respond and be willing to put their own data on the table. An industry that wants to move forward doesn't rely on one or two heroes — it relies on a crowd willing to blaze a trail together.

Point four: give AI a job description, and don't let it overstep.

AI can do a lot, but it can't do everything.

Companies have to get clear on which work goes to AI and which work must be done by humans. Livestream scripts, product detail page copy — AI can draft them, but the final polish and tone control have to be watched by a human, or everything that comes out tastes the same.

And AI's capabilities are changing, so your evaluation has to change with them. I'd even suggest writing AI tools into your HR planning as a "virtual employee." It has a role, it has boundaries of responsibility, and it gets regular performance reviews.

Point five: legal and data security — not a single line can be let slide.

Before using an AI tool, first confirm whether it has completed its service filing. When using it, strictly follow the rules on consumer privacy protection, intellectual property, and anti-unfair competition.

Best to set up a dedicated legal role, or bring in a professional lawyer, to run regular compliance reviews of the company's marketing activities and AI usage. At the same time, tighten internal management and keep track of what employees are doing online.

Compliance isn't a shackle — it's the lifeline that lets you go further.

A Final Word

After that dinner, my friend went quiet for a moment, then said:

"It sounds like AI isn't a question of whether to use it, but of how to use it."

Exactly.

What generative AI brings to cross-border e-commerce is a genuine, substantial opportunity. For companies that have pivoted from foreign-trade factories, that simultaneously juggle several platforms, and that also have to run livestreams — this opportunity is especially large.

But opportunity never guarantees outcomes. Treat AI as a cure-all and pour it in recklessly, and it becomes a landmine buried in your business; treat it as a blade that needs a human hand to hold it, and it can help you cleave open new markets.

Tools will change, industries will change, but one thing won't. The ones who actually win are always the people who both dare to use the new tools and are clear-eyed about where those tools' limits lie.

Wishing you and your company a place of your own in this wave.