The Gist
- Suspicion erodes trust. Most consumers trust an ad less when they merely suspect it was AI-made, so brands that avoid AI content can still take the hit.
- Doubt spreads widely. Synthetic images and video have consumers questioning whether anything they see is real.
- Labels are arriving. Instagram, Tidal, ARIA, Anthropic and EU and California regulators are each moving to identify or restrict AI-generated content.
- Proof of people. Captions, bylines and behind-the-scenes content show consumers the humans behind a brand’s work.
- Trust-building AI. Recommendation and personalization uses build trust, but brands should watch the line as it moves.
Consumers have driven record-breaking adoption of AI apps—most recently of Meta’s Muse. At the same time, consumers are increasingly worried about the long-term effects of AI’s growing usage and expanding capabilities.
Indeed, the public relations nightmare for AI seems to be only getting worse:
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A steady drumbeat of mass layoffs that are attributed to AI investments has workers worried
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High unemployment among new college graduates is undermining confidence in the value of higher education and causing most young people to see AI more as a threat than an opportunity
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Electricity inflation, water shortages and noise pollution caused by AI data centers has become a national political issue and a climate change concern
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And recurring security violations and “escapes” by AI frontier models has some even worrying about the stability of governments and society at large
Related Article: AI Has a Public Relations Emergency — and It’s Getting Worse
All of those issues aside, the core issue for marketers is whether AI usage improves their results.
Why Does AI’s Public Image Problem Matter to Marketers?
Layoffs, data center strain and frontier model security lapses are worsening public sentiment toward AI, and marketers now need to know whether AI use helps or hurts their results.
Consumers Distrust Ads They Suspect Are AI-Generated
According to The Harris Poll, 78% of consumers globally say AI makes ads “feel less authentic.” Given the premium that younger generations put on authenticity, that’s a damning statement about the potential damage AI-generated content can do to brand perceptions.
That same survey found that 73% of consumers say they’re “less likely to trust an ad” when they suspect it was made using AI. And that’s where we get at the primary problem: AI-generated content compromises brand trust for most consumers.
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Even worse, trust is compromised when consumers suspect content is AI-generated. That means some brands using AI-generated content may escape unscathed, while others who aren’t using AI for content generation are unfairly criticized.
In some circles, using AI-generated content is akin to a moral failing—to put it mildly—so the degree to which trust can be lost is very much a sliding exponential scale.
How Do Consumers React to Ads They Think Are AI-Generated?
Most say AI makes ads feel less authentic and trust ads less when they suspect AI involvement, which means brands can lose trust even when they haven’t used AI.
Synthetic Media Leaves Consumers Doubting What Is Real
Because AI can make an image or video of almost anything, consumers are now questioning everything they see.
According to research by the Human Clarity Institute, 86% of adults worldwide say AI-generated media makes them less certain about what is real. Plus, 96% say they worry that AI-generated media makes it easier to deceive people. That concern clearly extends to themselves in many cases, as 48% say they sometimes avoid content because they do not know what to believe.
How Is Synthetic Media Changing What Consumers Believe?
Because AI can fabricate almost any image or video, consumers doubt what they see, worry about deception and sometimes avoid content altogether.
How Platforms, Industry Groups and Regulators Label AI Content
Platforms of all stripes realize that a lack of trust is a major problem that threatens their future viability, so some are jumping into action.
Social Platforms Label AI-Generated Profiles and Posts
Bots and fake accounts have been staples of social media for a long time, and platforms have been hesitant to crack down on anything that isn’t outright malicious for a variety of reasons (including the fact that they make their account and activity numbers look better). However, AI has turbo-charged both bot-activity and fake accounts to the point where it’s seen as a more urgent problem.
For instance, Instagram is now putting a “AI-generated profile” label on accounts created using AI. It’s also been tagging posts that include AI-generated content.
Related Article: X, Meta and the Great Social Media Meltdown
Music Streamers Label and Demonetize AI-Generated Tracks
Content services like YouTube are already filling up with AI-generated content. While some see AI content as just content, others are taking a stand on behalf of human-made content. For example, music streaming service Tidal launched an AI policy that (1) labels AI-generated music, (2) allows users to block AI-generated music and (3) doesn’t allow AI-generated music to be monetized on its platform.
Music Chart Bodies Require Human-Made Recordings
Here, again, the music industry has been among the first-movers. The Australian Record Industry Association (ARIA) has banned AI-generated music from their music charts and from eligibility for their awards, requiring music to be “substantially human made.” That means that “Humans wrote the song and performed the lead vocal and the primary instruments.”
That move was made in response to an AI-generated remix of Madonna’s Like a Prayer going to No. 2 in Australia in May.
AI Model Makers Add Invisible Watermarks to Output
AI models themselves are trying to be a part of the solution by improving the traceability of AI-generated content. For example, Anthropic has started adding digital watermarks to content processed by their tools.
EU and California Laws Mandate AI Content Disclosure
Of course, some of those actions have been driven by new laws and regulations, most notably the EU Artificial Intelligence Act, which mandates transparency. The bottom line of that law is that “users must be informed when they are interacting with an AI system or where content is AI-generated.” In the US, the California AI Transparency Act has a similar goal.
To be clear, all of this is only the first wave of efforts. Brands should expect more to come.
Who Is Moving to Label or Restrict AI-Generated Content?
Social platforms, music streamers, chart bodies, AI model makers and regulators in the EU and California have all introduced labels, watermarks, eligibility rules or disclosure mandates.
How Brands Can Prove Their Content Is Human-Made
For brands, using AI to create customer-facing content carries risk. However, brands are exposed to some of those risks even when they’re not using AI to generate such content if consumers suspect they might have.
That’s right. For a growing number of consumers, you’re guilty until proven innocent.
(And if you’ve been caught using AI content in the past—say, promoting how amazing your expensive beauty products are by using AI models with flawless skin—then that guilty stain may be very hard to shake.)
To stay authentic:
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Be selective about AI use for consumer-facing content. For instance, using AI to change background elements or make other minor changes to an image is unlikely to raise any eyebrows. But depending on your audience, it might. It’s critical to understand your audience’s sensitivities when drawing your lines for AI content usage.
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Use captioning. For models. For locations. For whatever makes sense. Think of it as the opposite of an AI disclaimer. If it’s a real person, place, or thing, clarify that it is. For instance, some apparel retailers disclose the names of their models, along with their measurements, but they’re often hidden in a “Sizing & Fit” tab or accordion. It’s probably wise now to make that information more visible.
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Use bylines. Bylines aren’t just for articles and blog posts—although you should absolutely be using them there too if you don’t want people to assume they were written by AI. If your newsletter is curated by someone, say so. If an outfit was curated by your stylist, say so. If a selection of products was curated by someone, say so. Bonus points for including a photo of them.
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Highlight employees and behind-the-scenes looks. If you’re an apparel retailer that’s launching your spring line, share some behind-the-scenes photos or videos from the photo shoot. If you’re launching a new product, show some of the product testing along with your product developers. Have your employees share advice related to whatever your company does. Put forward more human faces and show more of the human process.
All of that said, use of AI for production acceleration, personalization, and a wide range of other operations is expanding rapidly and raising fewer concerns and no trust issues. After all, no one’s angry about Pandora’s music discovery algorithm or Amazon’s “Customers also bought” product recommendations. Indeed, those AI features build trust.
That should be the question that brands ask themselves any time they use AI:
Where will this fall on the spectrum of building trust vs. risking trust?
Needless to say, brands should be increasingly wary of anything that risks trust. But they should also be careful about AI use cases that are perceived to have a neutral impact on consumer trust. That’s because the line will continue to move, so keep an eye on it.
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