New Research: Gen Z Attitudes on AI Use in Marketing and Advertising

In marketing, the AI adoption debate is basically settled. Gartner's 2026 CMO Spend Survey found CMOs now put an average of 15.3% of their marketing budgets toward AI, and 70% see becoming an AI leader as a critical goal for the year. This isn't just the laggards catching up, either. Among high-performing teams, 84% already use generative AI for creative development.

In this race to adopt AI for marketing and advertising purposes, one critical question arises: how do audiences feel about it?

Early signs say consumers don’t like it. Over the past two years, high-profile AI advertising campaigns have drawn real public backlash, from fashion brands criticized for AI-generated models to a major fast-food chain that pulled an AI-made holiday ad after complaints. The objections sound similar: lost jobs, art taken from real creators, and a general sense of "AI slop."

So we wanted to get past the anecdotes and measure the reaction precisely, among the generation most likely to define the next decade of consumer spending.

AI for marketing and advertising: The Gen Z POV

In July 2026, we ran a study on the Rival platform among 901 Gen Z participants across the US and Canada, drawn from our proprietary panels. Rather than a traditional survey, we used a mobile-first, conversational format, the same messaging-style experience Gen Z use every day. And full disclosure: AI tools were used along the way, from our Smart AI Probe and Thoughtfulness Scoring to AI Summarizer for open-ends.

Capturing quant and qual feedback in one seamless research experience lets us report not just how Gen Z feel, but why, and what they do next.

The full report, The Gen Z AI Backlash: How Young Consumers Really Feel About AI in Marketing, walks through key insights from the study. Here’s a couple that stood out.

How do Gen Z consumers feel about the use of AI for marketing and advertising?

The sentiment is lopsided, and not by a little. 74% of Gen Z tell us they react negatively when they realize a brand's marketing was made with AI. Only 8% react positively.

Our numbers aren't an outlier. They line up with a wider body of research pointing the same way. The IAB and Sonata Insights found a 37-point gap between the 82% of ad executives who assume Gen Z and Millennials feel good about AI ads and the 45% of those consumers who actually do. And a Tracksuit survey of more than 6,000 US consumers found just 18% feel positive about AI-generated advertising. Different samples and audiences, different methods, same direction of travel.

In our study, Gen Z participants indicate that their objections are about both the output of AI-generated advertising and what it represents. In their own words, Gen Z audiences say AI marketing reads as "soulless," "lazy," and a way for companies to cut corners and avoid paying real people. One participant put it bluntly, calling it "a cheap way out for companies to cut employees."

To Gen Z, an AI-made ad isn't a neutral production choice. It's a signal about what your brand values.

The "so what" for marketers: the efficiency you can measure on a spreadsheet has a reputational cost you probably aren't measuring at all. If your internal case for AI is built entirely on speed and savings, you are optimizing for the one audience, your own operations, while discounting the audience the work is actually for.

What actions do Gen Z consumers take when they detect AI use in marketing?

This is where the reaction stops being a matter of opinion and starts showing up in your revenue. In our study, 72% of Gen Z claim to have already taken at least one concrete action against a brand after encountering AI-made marketing:

• 50% have unfollowed or stopped following a brand on social media
• 49% have complained about a brand to friends, family, or online
• 48% have unsubscribed from a brand's emails or texts
• 43% have stopped buying from or using a brand altogether

When Gen Z detects AI use in your marketing, it can impact brand reputation, brand loyalty and, ultimately, revenue. But we also found that there’s some important nuances. For example, in our study, Canadian participants are more negative and more likely to punish a brand for AI use. Another example: older Gen Zs are more likely to feel negatively.

How can marketers use AI without turning off Gen Z consumers

Let me be clear about one thing: our study is not advocating that marketers abandon AI. As a top market research company known for innovation, we are advocates of AI and have AI tooling in our product. But our study shows that there’s an opportunity for marketers to be more intentional in how they incorporate AI into their workflows — and how they talk about it publicly.

In our study, we shared some actionable tips for leaders (including learning streams that research teams can explore), but here are three tips worth noting:

Keep a human in the loop.

Use AI where it genuinely helps, but not as a stand-in for human creativity. Skip the low-effort AI content, and make sure a named human marketer is accountable for whatever ships.

Don't outsource your brand voice to AI.

Turning data into a clean chart or speeding up production barely registers with Gen Z. Hand over your art, your storytelling, or your voice, and that's where you lose their trust.

Watch how you talk about AI, not just how you use it.

Their anger is really about jobs. Celebrate AI efficiency in the same quarter you cut your marketing team, and you hand Gen Z the exact story they already believe.

Tracking how Gen Z sentiment, preferences and attitudes on AI change

None of this is settled. Consumer attitudes toward AI are moving quickly, and not always in one direction. The tech keeps improving, disclosure norms are still forming, and Gen Z themselves are drawing an evolving line between AI use they'll tolerate and AI use they'll punish.

If you’re a marketing leader with a mandate to operationalize and scale the use of AI, it’s important to get ongoing insights on the emotions, motivations and preferences of your different Gen Z audiences. At the very least, doing a bit of message testing before talking about your use of AI could make a huge difference. But there’s also a lot of value in ongoing research programs — insight communities or syndicated research like the Emerging Consumer Index, for example.

It’s a tricky time for marketers: AI tools promise efficiency and cost-savings, but modern audiences like Gen Z are not necessarily on board. In many industries, including ours, AI slop is a real concern, as well as the impact of AI on jobs. That’s why talking to your consumers is what could make the difference between shipping something that gets blasted online and one that inspires the right action.