It started with a backlash.
Mango’s AI-driven campaign, featuring hyper-realistic AI models that didn’t exist, sparked online outrage. Comments like “False advertising!” flooded social media. Consumers felt deceived, and Mango’s attempt to save time and money came at the expense of something far more valuable: trust.
Meanwhile, Dove was making waves for the opposite reason. The brand publicly committed to never using AI-generated models, staying true to its long-standing value of authenticity. The decision earned widespread praise, positioning Dove as a champion of trust in an era of increasing artificiality.
Two brands. Two choices. Two vastly different reactions. These contrasting stories highlight a critical crossroads: in their pursuit of efficiency, how much authenticity can marketers afford to sacrifice?
And yet, another question still lingers: Does it even matter?
What consumers really value
Over the last few years, creator-led content has become the gold standard of brand authenticity. Spurred by the saturation of traditional media environments and the rise of TikTok, creators and influencers have become a gateway for brands to reach micro-communities. The global influencer marketing market reached $24B in 2024 and shows no sign of slowing down.
At the same time, the industry is increasingly leaning on AI to meet the ever-growing insatiable demand for content. Generative AI tools are creating product images with hyper-customized models, while platforms like TikTok introduce AI-generated avatars that blend seamlessly into the ecosystem of user-generated content. Even influencers are turning to AI to scale their output, from automated editing to the creation of virtual clones, allowing them to meet the demands of brands without sacrificing personal bandwidth.
Marketers now face a decision: Does AI kill authenticity? Or is it just another evolution of content creation?
Because here’s the paradox: while consumers say they care, their actions don’t always match their words.
We’ve seen this disconnect in other areas, like privacy. Surveys show that 86% of people want greater control over how their data is used, and 78% say they’d stop engaging with a brand that failed to protect their privacy. But real-world behavior tells a different story: after a data breach, only 11% of consumers actually cut ties with the brand.
The lesson is clear: while consumers claim to value trust and ethics, their wallets often prioritize convenience and price.
How should marketers navigate this seeming conflict between values and technology?
1. Own your AI narrative: AI’s presence in marketing is inevitable, but brands that hide it risk backlash when consumers find out. The solution? Own it. Just as brands once labeled retouched images to maintain credibility, consider labeling AI-generated content—especially in industries where trust is paramount (e.g., beauty, healthcare, and finance).
Further, you can A/B test AI transparency labels and messages for ultimate impact (e.g. inspired by Apple’s “Designed in California. Made in China,” how would “Designed by People. Scaled by AI” land with consumers?)
2. Define your AI “Safe Zones”: Not all AI use cases are equal. A consumer healthcare brand using AI-generated models instead of real people? Risky. Using AI to adapt creative for different demographics, localize content or speed up production? Smart.
The key is establishing internal guidelines where AI is additive versus where it dilutes brand trust. AI usage needs to align with your brand values so your ultimate AI strategy reflects your broader brand promise.
3. Give consumers a reason to care: Every marketing decision should start with a simple question: Who are my consumers and what do they care about? If a brand’s AI-powered efficiency translates into better pricing, faster service or improved personalization, it can offset concerns about authenticity.
So far, the conversation around AI has been internal—focused on operational efficiencies rather than consumer benefits. It’s time to engage consumers directly in reimagining their experiences with AI and bring them along for the ride.
AI-driven content is here to stay. But trust? That has to be earned, continuously.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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