AI has slipped into every stage of the purchasing journey: instant recommendations, intelligent filters, automated comparison tools, conversational engines…
And with the arrival of Atlas, OpenAI’s browser capable of observing, remembering, and suggesting, the line between assistance and automated decision-making is thinner than ever.
But one essential question remains:
👉 When an AI influences a consumer’s choices, who bears the legal responsibility?
And what really happens to the data it collects?
⚖️ AI and e-commerce: an intermediary… without a defined legal status
On a traditional e-commerce site, the legal framework is clear:
- Transparency around partnerships and sponsored placements
- Liability of the seller in case of error or defect
- Mandatory consumer information obligations
But what happens when an AI engine, integrated into a retailer’s ecosystem or a browser like Atlas, suggests a product without the user knowing:
- whether the recommendation is based on relevance,
- detected preferences,or
- commercial parameters?
We are dealing with an algorithmic intermediary a role the law has not yet precisely defined.
Is it a neutral tool?
A decision-support interface?
A commercial recommender?
Depending on the qualification, the resulting liabilities vary considerably—yet none of these legal categories clearly apply today.
🔐 Atlas and personal data: a risk that cannot be ignored
➡️ Atlas can access page content and retain browsing patterns—even in incognito mode.
In an e-commerce environment, this raises several questions:
- How can the purpose limitation principle (Art. 5 GDPR) be upheld when an AI combines browsing, context, and history?
- How can users be properly informed (Art. 13 GDPR) if the system captures signals they cannot see?
- How can data security (Art. 32 GDPR) be guaranteed if technical vulnerabilities are documented, including in public tests?
This is not alarmism: these questions arise directly from the functionalities described.
And more importantly, they extend far beyond the browser itself they affect the entire e-commerce ecosystem.
🧭 Recommendations: the line between guidance and influence
On a traditional online store, a professional must disclose:
- when a placement is sponsored,
- when a recommendation is tied to compensation.
With an AI capable of suggesting a product “spontaneously,” how can we verify that the recommendation is genuinely impartial?
This is not just a commercial issue:
👉 it touches on the very foundation of information fairness, a core principle of consumer law and digital regulation.
In a system where decision criteria are opaque, how can we ensure that a consumer is not unknowingly steered toward a partner product or one with higher margins?
💡 A powerful technology… but a legal framework still catching up
The law evolves more slowly than systems capable of automating purchasing decisions.
We must therefore ask:
👉 How do these solutions influence our decisions, and
👉 Who is accountable when they mislead or misdirect.
