Ghada Ismail
Ahmad Abu Zannad is an advertising strategist and author of AdEntity, a new book arguing that advertising did more than sell products over the past century; it helped build modern identity itself, turning ancient human signals like status, belonging, and ambition into a shared language understood across cultures. The book’s central warning is that this role is now shifting to algorithms, which Abu Zannad argues are moving beyond shaping what we buy to shaping who we become.
In the first installment of Sharikat Mubasher’s interview with Abu Zannad, we explore the deeper forces shaping brand-building today: how culture actually works (and how startups misread it), what has really changed as advertising has moved from the TV era to the age of AI, and why an obsession with algorithms and data can quietly replace understanding people with merely measuring them.
Your book looks at how advertising became deeply connected to culture and technology. How can startups use culture to build brands that people genuinely connect with?
“I would start by changing one word in the question. I don’t think startups should use culture. I think they should understand it.
Culture is not putting a local celebrity in an advertisement, borrowing a dialect, or adding familiar symbols to a campaign. Those are expressions of culture. Culture itself is much deeper. It is the shared understanding of what success looks like, what generosity means, what makes somebody trustworthy, what feels prestigious, what feels embarrassing, what belongs and what does not.
And beneath culture sit very old human motivations.
People everywhere want belonging, recognition, security, status, love and hope. But cultures give those motivations different expressions. Ambition in Riyadh does not necessarily look exactly like ambition in London or Tokyo. The human motivation may travel; its cultural meaning changes.
And when I say culture, I don’t only mean national culture. Internet culture, youth culture, creator culture and subcultures are cultures too.
Look at Dollar Shave Club. They entered shaving against companies with enormous budgets and decades of category authority. They couldn’t outspend Gillette, so they understood something happening culturally: people were increasingly suspicious of over-engineered products, corporate language and inflated prices. Their famous low-budget 2012 launch film spoke in the irreverent language of internet culture and generated 12,000 new subscribers immediately after launch.
Or look at Liquid Death. They entered perhaps the ultimate commodity, water, and behaved nothing like a water brand. They borrowed the visual codes, humour and attitude of punk, heavy metal and energy-drink culture: tall cans, a skull, “Murder Your Thirst,” absurd entertainment. The founder has explicitly described the ambition as building an entertainment company that monetizes through beverages.
PRIME did something different again. Logan Paul and KSI entered one of the world’s most competitive beverage categories with something Coca-Cola and Pepsi could not simply manufacture overnight: an existing cultural relationship with millions of people. The product launched in 2022 out of creator culture, turning two former rivals into partners and their audiences into an extraordinary distribution network for attention.
None of these companies began with the advantages traditionally needed to enter such categories. What they possessed was cultural capital before they possessed category power.
That is where I think startups have an interesting advantage over very large companies. They may have less money, but they are often much closer to the tension they are trying to solve. The founder may have lived the frustration, spoken the language of the community and understood a behaviour long before somebody turned it into a market-research chart.
So I would tell a startup: don’t begin by asking, “How do we make our brand culturally relevant?”
Ask: What is already alive in culture that nobody in our category is seeing… and what legitimate role can our product play inside it?
Because if you cannot outspend the category, you may still be able to out-understand it culturally.
The best brands do not impose themselves on culture. They find something already alive within it… and become useful enough, meaningful enough and distinctive enough to belong there.”
From the traditional advertising era to today’s AI-driven landscape, what has changed most about how brands earn consumers’ attention, and what has remained the same?
“I think the biggest change is that we have moved from an age of persuasion to an age increasingly shaped by selection.
In the traditional advertising era, a brand would buy access to an audience through television, newspapers, magazines or outdoor, and then the creative idea had to do the difficult part: make people notice, remember, feel something and perhaps change their behaviour.
There was still a human author in the middle of that process. A strategist, a writer, a creative director, a filmmaker. Someone was making a judgement about people and culture and saying: I think this idea will matter.
Today, the system is very different.
The algorithm increasingly decides what reaches you, how often you see it, what disappears, what gets amplified and what comes next. And AI is accelerating this dramatically. We can now create hundreds or thousands of variations, personalize them, test them in real time and optimize continuously around whatever generates a measurable response.
So the machinery of attention has changed enormously.
But the strange thing is that the human being underneath it has changed very little.
We still want many of the things our grandparents wanted: belonging, recognition, status, love, security, hope, companionship, achievement. This is one of the central arguments in AdEntity. Advertising did not invent these desires. At its best, it understood them, translated them through culture and gave them contemporary symbols, products and stories.
A diamond could become a signal of commitment. A car could become a signal of achievement or freedom. A sports brand could turn effort into a story of personal transcendence.
The technology changed. The human motives did not.
And I think that distinction matters enormously now because AI creates a temptation to confuse response with meaning.
An algorithm can learn that outrage keeps me watching. It can learn which image makes me click, which headline makes me pause and which version converts 3% better. But a reaction is not necessarily a relationship. And attention is not necessarily admiration.
This is where I worry about the direction of advertising. We are becoming extraordinarily good at optimizing the signal while sometimes forgetting to ask whether the signal means anything.
The old advertising industry could certainly produce terrible work, but its greatest work tried to create something people would voluntarily carry into culture: a line, a story, an aspiration, a piece of music, an image, sometimes even a new way of seeing themselves.
The danger today is that we settle for something much smaller simply because we can measure it more precisely. So if I had to put the whole transition in one sentence:
The old challenge was, “How do I persuade you?” The new power is increasingly, “What will the system keep showing you?”
That is an extraordinary technological shift. But brands should remember that behind every data point is still a very old human animal trying to belong, aspire, love, achieve and make sense of the world. The screen keeps changing. The human being behind the screen changes far more slowly.”
Has advertising become too obsessed with algorithms and data at the expense of understanding people? What can startups learn from that?
“Yes, but I would be careful with the criticism because I am not against data, algorithms or AI. Quite the opposite. I think they are extraordinary tools.
The problem begins when we confuse efficiency with intelligence.
Years ago, in Adman vs. Chomsky, I challenged Noam Chomsky’s description of advertising as an industry whose prime task is to ensure that “uninformed consumers make irrational choices.” I still disagree with that as a definition of advertising. Human beings were irrational long before the first advertising agency existed. Behavioural economics has simply helped us understand some of the shortcuts through which people navigate a complicated world.
But there is a danger today that we take those cognitive biases; scarcity, social proof, loss aversion, immediacy, outrage, fear of missing out… and hand them to an algorithm whose only instruction is: find what produces a response and do more of it.
Then AI allows us to generate another hundred versions, test them faster, target them more precisely and optimize them continuously.
We should ask ourselves: is that progress?
Or have we simply become better at doing mediocre advertising faster, cheaper and more intrusively?
That, to me, is the misuse of the algorithm. Because there is another possibility.
Look at Sleep or Die, a young sleep brand that looked at an entire category filled with lavender colours, peaceful bedrooms and soft wellness language and basically said: this is not what insomnia feels like. The brand called exhausted customers “zombies,” used provocative cigarette-style packaging and built an entire irreverent world around the seriousness of sleep. One unconventional product post on LinkedIn reportedly reached more than 180,000 people, and around 4,000 people joined the waitlist before launch.
The algorithm did not come up with that idea. It discovered that people found the idea interesting.
And Dubai gave us an even more extraordinary example.
FIX Dessert Chocolatier did not begin with a dashboard saying, “Pistachio content has a high completion rate.” Sarah Hamouda began with a craving and created something genuinely different: chocolate, pistachio, tahini, and the crunch of knafeh. Then a creator filmed herself breaking the bar open. You could see the green filling, hear the crack and crunch, and almost experience the texture through the screen.
That video eventually exceeded 120 million views, and FIX reportedly received more than 30,000 orders after it took off. The phenomenon became so large that “Dubai chocolate” became a global food category, copied by some of the world’s biggest confectionery companies.
Again, the algorithm did not invent Dubai Chocolate. It recognized that human beings could not stop looking at it.
Crumbl is another useful example. Its weekly rotating cookie drops created anticipation and FOMO before TikTok amplified them; on the platform, its campaign reached 22 million people and grew followers by 1,500% in two months. The interesting part is that the platform was amplifying an existing behavioral idea, the weekly drop, not substituting for one.
And that is what I think startups should learn. Don’t ask AI to compensate for the absence of an idea. Don’t use behavioral science merely to locate the next vulnerability you can press.
Understand people first. Create something distinctive enough to deserve attention. Then let the algorithm do what it is exceptionally good at: find the people for whom that idea resonates and help it travel.
The algorithm should be an amplifier, not the strategist. And perhaps that is the simplest way I can put it: AI should help great ideas travel faster. It should not merely help mediocre ideas become cheaper.”