Is your brand disappearing in the AI era?

We’ve all heard that a picture says a thousand words. Now those words are being read by machines. And that changes everything.

In 2025, a growing share of product discovery began inside AI systems rather than traditional search engines. People no longer scroll through links. They ask direct questions:

• Which electric car is the safest?

• Which brand is truly sustainable?

• What product should I choose?

AI doesn’t return blue links. It returns answers.

And those answers are built on multimodal interpretation — text and images.

Your visuals are no longer decoration. They are training data.

AI Doesn’t See Aesthetics. It Sees Signal Density.

For decades, brands optimized imagery for humans:

• Does it look premium?

• Is it consistent?

• Does it feel right?

AI evaluates something else.

It detects patterns. It reinforces repetition. It translates visuals into semantic meaning. Every image increases or decreases the probability that your brand stands for something specific.

To AI, no image is neutral.

And this is where many brands are quietly exposed.

A Simple Test: Safety

Close your eyes and think of a car brand that stands for safety.

Most people think of Volvo.

That association is not accidental. Volvo built decades of communication around safety — starting with the three-point seatbelt, which they chose not to patent so everyone could benefit.

We asked a simple question: How many of those images clearly communicate safety?

• Direct safety visuals: 0

• Weak, indirect cues at best: 1–2

That means roughly 25 out of 27 images communicate design, urbanity and modern electric mobility — but not safety.

This is not a design flaw. It is a signal imbalance.

Humans may still associate Volvo with safety because of decades of brand building. AI does not inherit history. It learns from visible repetition.

When someone asks an AI system, “Which electric car is the safest?”, the answer is shaped by signal density — not brand legacy.

Search will not reward what you used to stand for. It will reward what you consistently encode.

The Structural Shift

For decades, brand ecosystems were built exclusively for human perception.

Now they are parsed by machines that influence discovery, recommendation and visibility.

If your strongest brand pillar is not explicit in text, visible in imagery, and repeated consistently, it becomes fragile in AI-mediated search.

And fragility leads to invisibility. Not dramatically. Gradually.

What to do?

Here at Scenes, we approach this in three disciplined phases:

1. AI Perception Audit
Understand how major AI systems currently interpret your brand across text and imagery.

2. Signal Gap Analysis
Identify which brand pillars are underrepresented or semantically weak.

3. Visual Reinforcement
Strengthen the right signals — either by enhancing existing assets or developing new visuals designed for multimodal clarity.

Not to game algorithms. But to align your visual reality with your strategic identity.

A picture is still worth a thousand words.

But now those words are being read by machines first.
The only real question is whether your images are reinforcing your brand meaning — or fading into silence.

Let’s talk.

Sign up for a 30-minute online walk-through on how to turn your visuals into strong brand ambassadors. Contact Michael Rying

A Necessary Clarification

This evaluation was conducted using ChatGPT 5.2 as the interpretive model. A comprehensive GEO audit should also include other major AI systems such as Claude, Gemini, Grok and additional AI search agents, since architectures and weightings differ.

However, all modern multimodal systems share the same foundation: they convert images into semantic meaning and reinforce repeated signals.

If safety is not clearly visible, it will not be strongly inferred.

Weak signal in. Weak association out.