🤖 AI-Powered Advertising: Ethics and Privacy
How to balance innovation and privacy in AI-driven campaigns
You browse the internet and come across an ad that feels like it’s reading your mind, recommending exactly the product you were looking for. That “magic” is already a reality: around 69% of marketing professionals use AI in their operations, and nearly 20% allocate more than 40% of their budget to AI-driven campaigns.
And I’m not talking about cookies and retargeting here…
GPT, Grok, and others have made AI mainstream and accelerated its adoption. Campaigns powered by generative AI have shown real potential to captivate audiences, cut costs, and drive innovation.
Just like in the image from this post : Imagine walking down the street under a 50°C sun, and you see a woman on a giant screen at the beach drinking an ice-cold Coke. I don’t know about you, but in that context, I’d probably buy any drink.
But along with the excitement come ethical challenges. As AI becomes more embedded in advertising, concerns grow around privacy and data protection, algorithmic bias, and consumer manipulation. Even with new privacy regulations, over half of companies still fail to offer basic transparency, and many don’t even provide users a copy of their own data when requested.
Algorithms trained on biased data can produce discriminatory outcomes. An AI model can also hallucinate false content or go overboard with persuasive messaging, potentially misleading viewers. And these failures don’t always come from bad actors, well-designed systems can still behave in unpredictable ways.
So how can we use AI in advertising both ethically and effectively?
It starts with accountability. Leading companies in this space are already implementing responsible AI policies with cross-functional teams. They emphasize transparency and human oversight during critical stages to keep the technology aligned with human values.
Does that make sense?
From a technical standpoint, practices like algorithm audits, bias detection tools, and continuous training with diverse datasets help prevent injustice and errors.
When it comes to user data, sometimes less is more.
With browsers phasing out third-party cookies, the old tracking model is (hopefully) on its way out.
Advertisers are now focusing on first-party data (collected directly from users) and zero-party data (voluntarily provided by users), paired with contextual targeting—ads based on the content of the page, not personal profiles.
Research shows that this approach can still deliver strong results without identifying individuals. Contextual ads can make up for the lack of personal data while maintaining ad performance and ROI.
Mark Zuckerberg’s recent claim, that AI will render media agencies obsolete, sparked a wave across the advertising industry. In his view, any business could just hand over its budget to Meta, and AI would take care of everything: creation, targeting, execution, no humans needed. It's the promise of a magic button that turns money into performance, without the advertiser needing to understand the audience, craft content, or rely on specialists. But while tempting for some, this narrative completely overlooks the true complexity of communication. Advertising isn’t just about stats—it’s about context, culture, emotion, timing, and differentiation, all things AI doesn’t yet fully grasp.
In my humble opinion, Zuckerberg’s statement says more about platform ambitions for ecosystem control than it does about the real capabilities of AI.
If the future of advertising is more automated, it will also demand more ethics, creativity, and transparency. And that can’t be bought with a single prompt. Agencies that embrace AI as a partner, not a replacement, will remain crucial for brands aiming to build something meaningful and lasting. The term “med-AI-a agencies” captures the idea well: it’s not about removing people, but about raising the bar with technology as an ally.
The future of digital advertising promises AI everywhere, from generative content to predictive algorithms, while privacy and transparency become competitive advantages. Trends like hyper-personalization and automation will evolve alongside rising public expectations: if consumers know AI is behind the ad, they’ll also expect more respect and clarity in how their data is used.
Companies that invest in explicit consent, data protection, and model explainability will earn user trust.
In my point of views, the future will be:
Tracking-free advertising will be the new normal: With third-party cookies disappearing, strategies will rely on contextual targeting and first-party data sources, like loyalty programs and email lists (think Substack), emphasizing privacy from the start.
Generative AI as a creative engine: Campaigns will be created, optimized, and adapted in real time using AI, which will generate texts, images, and videos on demand, and predict consumer behavior with high accuracy.
Immersive experiences at scale: Brands will shift from banners to augmented reality, virtual reality, and maybe even the metaverse (but not that awkward pandemic version), offering interactive experiences where consumers live the brand message instead of just seeing it.
Sustainability and ethics as a competitive edge: People want campaigns that feel real, inclusive, and purpose-driven. Brands that overdo greenwashing or misuse AI will lose credibility, and sales.
Decentralized influence and conversational content: Micro-influencers, user-generated content, and AI-powered conversational interfaces (like chatbots) will transform how brands connect and engage.
It’s time to reinvent marketing: The “collect data first and apologize later” mindset is out. Context with consent is in.