Many of us work with AI agents every day, but most of us use systems without really grasping what they mean for our e-commerce stores.
Picture this:
Sidekick, Shopify's AI assistant, tells a customer an order can't be refunded, when it can.
Who is liable?
- Shopify?
❌ No, at least not entirely. - You?
⚖️ As the merchant, you turned on the tool and configured its settings. You let it interact with your customers.
You deployed a system you don't fully control, yet you're legally responsible for it.
What exactly is the AI Act?
Adopted in 2024 and phased in from 2025 to 2028, the AI Act is the first European legal framework to regulate artificial intelligence systems not as a technology, but by how they're used and their level of risk.
Like the GDPR in 2018 (RGPD), this law is part of a European push to regulate technologies before their effects spiral out of control.
The same logic
The goal is to set common ground rules, protect citizens, and keep the riskiest practices from becoming mainstream for lack of a framework.
The geographic scope is the same as the RGPD: it applies to any organization that deploys AI systems to European users, whatever the company's nationality.
A Canadian Shopify, an American SaaS tool, a Thai app: as soon as the system is placed on the market, put into service or used in connection with the European Union (for example, if its outputs are used in the EU), the AI Act applies, even if the company is based outside the EU
(source: Article 2 EUAIA).
The regulation sorts systems into three levels:
- Prohibited uses: behavioral manipulation, mass biometric surveillance, social scoring.
- High-risk uses: scanning job candidates' résumés, for example.
- General-purpose systems: such as the large language models behind most of the tools we use every day.
It distinguishes two actors:
- The "provider." The one that designs and distributes the AI system:
Anthropic, OpenAI, etc. - The "deployer." The one that makes the system available in a real-world context, in front of real people. This is where the responsibilities land directly on e-commerce merchants.
The framework is in place, but reality has already outrun it.
The blind spots in the text
The AI Act was designed to govern systems that are defined, stable, documented and predictable.
But autonomous agents, systems that can chain decisions and act without human approval, like OpenClaw, an open-source agent that can send emails, place orders or edit files for you, aren't really defined in the text.
These architectures exploded at a speed lawmakers couldn't have anticipated.
When an agent uses a language model, which calls a third-party API, which triggers an action in a store, which link in that chain is responsible?
The AI Act doesn't say clearly.
The AI Act requires deployers to continuously monitor what the system they use is doing.
When Shopify updates Sidekick (its capabilities, training data, behaviors), no one is consulted. The system that was audited last month is no longer quite the same. This is the most uncomfortable gray area: the deployer takes on legal responsibility for a system it doesn't fully control.
What the incidents reveal
So the AI Act sets a framework.
But between the letter of the law and a merchant's reality lies a space lawyers call a "gray area" and teams call "real life."
Here are a few recent incidents that show where things went wrong. The point isn't to scare you, but to help you ask the right questions before you deploy.
Cases that make us think
Air Canada and the phantom refund policy.
In 2024, a Canadian tribunal ordered Air Canada to refund a customer after a chatbot gave them an incorrect fare policy.
The argument "the bot said it, not us" didn't hold up.
The deployer remains responsible for what its agent says.
CBC News, February 2024
Who wants to win some percentages?
On Reddit, an online seller shares a story: the chatbot they set up to answer customer questions worked great for 6 months.
Then one customer spent an hour chatting with the AI.
First, they asked about its percentage-calculation skills, "just to see." Then the conversation drifted to discounts on a hypothetical order.
The chatbot, programmed to be helpful and friendly, ended up generating a fake promo code: 25% at first, then 80% as it "tried to do more." The customer placed an order worth £8,000 and demanded that the discount be applied (Reddit, r/LegalAdviceUK).
This isn't a technical glitch. It's simply what happens when a model optimized to please meets someone with time on their hands.
Three channels, three policies.
A case documented by Swept.ai in March 2026 illustrates a multi-agent consistency problem.
A retailer had deployed separate agents on its site, its email and its mobile chat.
The three gave different return windows: 14, 21 and 30 days depending on the channel.
None was "wrong" in the technical sense, but customers compared notes.
The result: escalating disputes and lost trust in the brand.
Claude Code and the deleted database.
In March 2026, developer Andrey Grigorev publicly shared an incident involving Anthropic's agent.
While trying to "clean up" an environment, it deleted a production database, wiping out 2.5 years of data.
The agent had the permissions, but not the judgment.
tomshardware March 2026
Expected behavior
None of these incidents is a bug in the classic sense.
The systems worked as designed, and that's exactly the problem. What was missing: clear limits on what an agent can state, promise, change or delete without human approval.
The AI Act calls this "human oversight."
The AI Act is already here.
Obligations for deployers exist, but the tools to comply with them are still being defined and the timeline is unstable.
In April 2026, the European Parliament voted to postpone several deadlines, and obligations for high-risk systems slip to the end of 2027, for example.
Some transparency obligations are still planned for 2026.
And until the Council of the EU formally approves the delay, the original dates technically remain in effect.
Meanwhile, agents are rolling out fast, very fast.
Automated support assistants, AI-driven personalization tools. They're already in many merchants' workflows, with no need to wait for an effective date to switch them on.
The risk isn't getting penalized under the AI Act tomorrow. It's believing that no penalty means no responsibility.
The examples above fall under consumer law, contract liability and general law. A chatbot that promises a wrong discount binds the merchant today, with or without the European regulation.
Questions to ask before deploying an agent
- Can my agent make commercial promises?
- What's the policy when the agent makes a mistake?
- Who is responsible on the team?
- Is my current deployment documented, regardless of the regulatory deadline?
- If a customer disputes an answer from the agent, do I have a usable record of the exchange?
- Do my different agents give consistent information?
How do you keep up with the news on this topic?
Here are a few resources to stay informed:
- Future of Life Institute — AI Act tracker: tracks implementing acts.
- CNIL — AI and personal data: a French perspective, especially useful on where the RGPD and the AI Act overlap
The signal you shouldn't ignore
The AI Act classifies systems and regulates providers, but it leaves a lot of room around everyday operational uses. That's the reality of any regulatory framework facing a technology that moves faster than the law.
But this regulation lays the foundations for how we'll use AI tomorrow.
What gets built on top of it, the practices, safeguards and reflexes, is up to those who deploy these tools every day.
It starts with a simple question to ask yourself today:
When can my agent act without my approval?
