We've spent the last few years sticking a little sparkle icon on AI features and calling it transparency. A shimmer here, a tooltip there — done. But here's the thing: that was never transparency. It was decoration. And regulators have noticed.
So what's actually changed?
The EU has issued new guidelines on how AI-powered products and features need to be labelled. The upshot: vague, decorative indicators won't satisfy the requirements. Labels need to be explicit, contextual, and genuinely informative. Users must clearly understand when they're interacting with — or consuming — AI-generated content.
The full implementation details are still emerging, but the direction is unmistakable. If you're building products for a European audience, and most of us are, this affects your design decisions now.
This isn't a legal problem — it's a design problem
Here's what makes this interesting: the guidelines aren't prescribing specific UI patterns. They're setting an outcome — meaningful user understanding — and leaving it to product teams to figure out how to get there. That makes it a design challenge, not a compliance checkbox.
And it's a challenge we should have been tackling already.
Think about how most products currently handle AI disclosure. There's a sparkle icon next to a feature name. Maybe an "AI-powered" badge somewhere in the marketing copy. Occasionally a brief tooltip if you hover in exactly the right spot. But does the user actually understand what the AI is doing? Do they know whether the text they're reading was written by a person or generated by a model? Do they grasp the limitations?
Usually, no. Not even close.
We've been treating AI labelling as a branding exercise — a way to signal innovation rather than inform users. The sparkle icon doesn't say "this content was generated by a language model and may contain inaccuracies." It says "✨ ooh, fancy tech ✨." Those are very different messages.
What does honest AI labelling actually look like?
It depends entirely on context. That's what makes this hard — and what makes it real design work rather than a one-size-fits-all badge.
A search result that's been AI-summarised needs different disclosure than a product photo that's been AI-enhanced. A chatbot response needs different labelling than an AI-suggested email subject line. The stakes are different, the user's expectations are different, and the consequences of misunderstanding are different.
Some questions worth asking about every AI-powered feature you're designing:
- What specifically is the AI doing? Generating content? Ranking results? Making a recommendation? Each deserves different communication.
- How reliable is the output? If the system is guessing, the user deserves to know.
- Can the user distinguish AI-generated from human-created content? If not, why not?
- What's at stake if the AI gets it wrong? The higher the stakes, the more explicit the labelling needs to be.
You can't answer these questions with an icon. They require the kind of contextual, thoughtful design work that considers the user's mental model, their expectations, and what happens when things go sideways.
Why this is actually good news
I know — "new EU regulation" doesn't exactly spark joy. But this might be one of those rare cases where regulation pushes us toward genuinely better design.
Users are increasingly sceptical of AI-generated content. They want to know what they can trust. If your product earns that trust through clear, honest communication about where AI is involved and where it isn't, that becomes a competitive advantage — not just a compliance burden.
The products that get AI labelling right won't just avoid regulatory trouble. They'll build the kind of user trust that's becoming genuinely scarce. And trust, it turns out, is a pretty good differentiator.
Try this: an AI disclosure audit
There's no off-the-shelf tool for this yet, and that's kind of the point. But here's something concrete you can start today: create an AI disclosure audit for your product.
For every feature that uses AI, document three things: what the AI does, what the user currently sees, and whether a reasonable person would understand what's happening. If you can't explain it clearly in that document, your interface probably can't explain it clearly either.
It's not glamorous work. But it's the kind of structured thinking that separates considered design from feature shipping.
The sparkle era is ending
Pull up any AI-powered feature you've shipped or are currently designing. Ask yourself honestly: does the user genuinely understand that AI is involved, what it's doing, and where it might fall short?
If your answer boils down to "well, there's a sparkle icon" — you've got design work to do. The good news? This is exactly the kind of problem designers are built to solve. So let's actually solve it.