Why Smart Brands Are Going All-In on AI Transparency

When “Ethical AI” Isn’t Actually Ethical

Last spring, Adobe made headlines for all the wrong reasons. The company that had positioned its Firefly AI tool as the “ethical alternative” to competitors like Midjourney was caught red-handed. During the process of training the Firefly AI model, some of the images came from competitor Midjourney: the very company Adobe had criticized for using questionable training data.

The irony was thick. Adobe had built its entire marketing strategy around being the responsible choice for enterprise customers who were “very concerned about using generative AI without understanding how it was trained.” Yet behind the scenes, they were cutting the same corners they publicly condemned. The question isn’t whether or not consumers will find out how we’re using AI: it’s when, and whether we’ll be ready for that conversation.

As marketers, we’re caught in a perfect storm. Consumer skepticism toward AI is high, regulatory scrutiny is increasing, and our industry’s credibility is already fragile after years of data privacy scandals and “black box” advertising algorithms. The numbers tell the story: 86% of Americans say transparency from businesses is more important than ever before, according to Sprout Social research. Meanwhile, 81% of consumers must trust a brand to buy from it, per the Edelman Trust Barometer. We’re asking consumers to trust us with AI-generated content at precisely the moment when trust has become our scarcest resource.

This matters especially for brands targeting the New American Middle, a pragmatic subset of American consumers who value authenticity. They’re not anti-technology, but they are anti-manipulation. And they have long memories for brands that burn them.

2. Creative Attribution

This hits close to home for creative agencies. Many AI tools are trained on datasets scraped from artists, writers, and photographers without permission or compensation. When clients discover this, it raises uncomfortable questions about our professional ethics.

But some companies are pioneering better approaches. Shutterstock has created a model that compensates artists when their work contributes to AI-generated content. Getty Images built their AI tool exclusively from their own licensed content. Adobe—despite their recent controversy—is working on more transparent sourcing for future models.

“Adobe basically wants to position itself as the superior alternative, but it also wants really cheap inputs, and AI is a really good way to get cheap [content],” Harvard’s Rebecca Tushnet explained to Bloomberg. That tension between ethics and economics is something every agency faces.

4. Cultural Context

Here’s where AI consistently fails: understanding real customer lived experiences. We’ve all seen the tone-deaf campaigns: luxury vacation ads targeting struggling families, blue jean ads that fall short, financial advice that assumes disposable income. It goes on and on.

One high-profile example came from Levi’s, which partnered with an AI company to generate synthetic models in the name of “diversity.” The move was widely criticized for sidestepping real representation, reducing inclusivity to an algorithm rather than investing in real people.

The most successful AI implementations we’ve seen combine algorithmic efficiency with human cultural intelligence. AI handles the routine tasks; humans handle the strategy, context, and cultural sensitivity.

Learning from Our Mistakes

Adobe’s Firefly misstep, while disappointing, doesn’t have to define the trajectory of ethical AI in marketing. Adobe’s acknowledgment of the issue and ongoing efforts to build more transparent sourcing models suggest that even industry leaders can course-correct when held accountable. This gives us hope that the broader AI ecosystem can evolve toward more ethical practices, not because companies suddenly develop consciences, but because consumer and regulatory pressure makes ethical AI the only viable path forward.

Every AI decision we make as marketers is a vote for the future we want to create. We can build an industry that uses AI to become more efficient at manipulating consumers, or we can use it to become better at serving them.

The choice we make will determine whether the next generation of consumers sees marketing as a trusted advisor or just another source of automated spam. It will determine whether the best creative talent wants to work in our industry or flees to more human-centered fields. Most importantly, it will determine whether we build sustainable competitive advantages or just participate in a race to the bottom on price and quality.