The Executive Belief vs Consumer Reality

Inside the industry, enthusiasm is high.

Research shows that roughly 80% of ad executives believe consumers feel positive about AI-generated advertising.

The problem is the consumer data tells a different story.

Separate studies show that two in five U.S. adults report a negative opinion of brands that use AI in advertising. Around 23% report feeling very negative.

That is not a marginal risk.

That is brand damage territory.

People Can See Through It

Another data point worth sitting with.

Around 57% of people cannot accurately spot AI-generated imagery.

Which means 43% can.

Nearly half your audience may detect something is off.

When trust is the foundation of your brand, that is not a small number.

Why the Distrust?

Part of the issue is association.

A large volume of AI-generated advertising online today is coming from low-trust operators. Think click-harvesting websites, questionable health products, low-effort articles padded with banner ads and uncanny visuals.

Consumers are building a pattern in their heads.

AI visuals often equal low quality, low effort, or low credibility.

That is not fair to responsible brands. But perception is what matters.

The 2025 Coca-Cola Christmas Ad Case Study

In 2025, Coca-Cola released a Christmas advertisement built heavily using generative AI.

Credit where it is due. It was bold. It experimented. It pushed the conversation forward.

But the reaction was instructive.

The ad was criticised as lifeless and soulless. Viewers described uncanny animals and digital textures that felt off. One version reportedly received around 30,000 dislikes to 2,300 likes on YouTube shortly after release, according to public dislike tracking extensions.

The backlash centred on one word.

Authenticity.

That matters for a brand built on nostalgia and emotional storytelling.

Innovation without taste control becomes a liability.

AI as a Tool vs AI as the Final Product

There is a critical distinction here.

Using AI tools to accelerate workflow, explore concepts, or generate scalable variations is one thing.

Using raw AI output as the final consumer-facing advertisement is another.

The first increases efficiency and experimentation.

The second directly touches brand perception.

These are not the same risk category.

The Real Risk: Fooling Ourselves

The biggest danger is not the tool.

It is self-deception.

When we generate something quickly, we can convince ourselves it is “good enough.” The speed can blur judgment.

This is where experienced creative oversight matters.

A strong graphic designer or art director can tell within seconds whether something feels off. Their pattern recognition for quality is deeply trained.

That filter is not optional.

Because if their feedback feels harsh, consumer reaction can be harsher.

The numbers already show that.

How to Use AI in Advertising Without Damaging Trust

AI is not the enemy.

Poor taste is.

If you are using generative tools in advertising:

• Run work through experienced creative oversight
• Pressure test it against brand values
• Be brutal about quality control
• If there is doubt, do not publish
• Consider transparency where appropriate

We have developed systems that automate ad and image generation at scale, allowing brands to produce and test variations efficiently.

But those systems include layered checks.

Human checks.

Brutal checks.

Because scale without taste is just amplified mediocrity.

Final Thoughts

AI in advertising is not a yes or no question.

It is a discipline question.

Consumers are not anti-technology.

They are anti-fake.

If your brand is built on trust, make sure every frame earns it.