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Yannick Bolloré, the CEO of Havas marketing group, usually enjoys a morning swim in the Mediterranean Sea during the Cannes Lions advertising festival. However, this year, he couldn’t access the beach due to the cabana-filled spaces occupied by Meta, Google, WPP, and other companies.
What began as a modest event nearly 70 years ago as an offshoot of the Cannes film festival has now expanded along the Croisette onto rented yachts and extravagant mansions. It has encompassed television, streaming, social media, technology platforms, and all aspects related to advertising. The festival now welcomes machine learning enterprises like OpenAI, known for their creations ChatGPT and Dall-E.
While sitting at WPP’s beach bar, I had the opportunity to hear Jensen Huang, the CEO of Nvidia, a trillion-dollar chipmaker, predict a revolution in the advertising industry driven by generative AI. He amazed the audience of marketers by stating, “You will create AI factories where creativity is the input and content is the output. You will produce billions of ads… individually customized for each person.”
In Cannes, this kind of optimistic outlook is always well-received, presenting a vision of the future where chief marketing officers can embrace innovative advancements. Cannes Lions now markets itself as an “international festival of creativity,” and no creative professional wants to be seen as a pessimist. In the sunny atmosphere, with a glass of rosé in hand, AI feels less like a job threat and more like an appealing possibility.
However, it’s important to be cautious of the AI hangover. The previous technology revolution in advertising, which promised remarkable efficiency and precise consumer targeting, was automated ad buying across the web. In reality, the ad tech industry, dominated by companies like Google, has had mixed outcomes.
This week, a trade group representing US advertisers complained that around a quarter of the $88 billion spent on automated ad buying goes to waste, with ads appearing on 44,000 websites, some of which are dubious. Peter Mears, head of Havas’s media agencies, reflected, “A decade ago, we took the niche audience approach with programmatic advertising and became infatuated with technology.”
Generative AI undeniably has practical applications in the creative realm of advertising. For instance, it can empower smaller businesses to compete with heavy marketing spenders like Mars and Diageo. The creative minds at the agencies occupying the most coveted spots in Cannes can be costly to hire; they have to fund all those parties somehow.
As an example, Sirius XM, a US radio broadcaster, plans to utilize AI to produce ads for small companies. They offer these businesses a selection of AI-generated pitches, which are then voiced by an AI instead of an expensive “voice talent.” The results may not be as persuasive as a human production, but they are cheaper and quicker.
Similarly, McCann Worldgroup, a marketing group, used AI to design 42,000 unique signs and menus for 8,400 owners of Mexican hot dog and hamburger stands, who are clients of Bimbo, the bakery group. While having an AI-generated fast food display may not elevate one to the level of McDonald’s or KFC, it certainly contributes.
AI can also assist in the inefficient process of campaign development for large companies. Instead of manually creating numerous initial ideas, AI can bring them to life and discard or store them in a database for future use once one or two options are selected. Humans would still be responsible for producing the final ad, with routine tasks automated.
However, the most exhilarating conversations at Cannes revolved around pushing the boundaries beyond AI integration. It involved Huang’s vision of infinite fragmentation or what Brad Lightcap, OpenAI’s COO, called a “Cambrian explosion” of creativity. (Our meeting took place in a café because OpenAI is so new in town that they don’t yet have a cabana, but they will soon.)
The idea is that marketers no longer have to show the same ads to everyone, regardless of who they are or what they are doing. AI has the potential to reduce the costs associated with making small variations, such as colors, shapes, and background music, based on our preferences and circumstances. For example, if I have a history of purchasing purple shirts, my ads are more likely to feature the color purple.
Advertisers find this concept intriguing, but there are obvious risks. One is that too much personalization can quickly become eerie. While I don’t mind seeing ads for similar brands on Instagram, if all the ads start mirroring me, it would feel unsettling. There are limits to how deeply I want the AI model to learn about me.
Beyond that, I question whether it’s truly worth it. While Nvidia’s chips may be capable of processing billions of individual ads, there aren’t that many reasons why someone would buy ice cream or ketchup. In reality, most people consume these products for the same reasons as everyone else, which is how advertising has always worked. Fragmenting ads may sound exciting, but is it practical?
Meanwhile, I sympathize with the future juries responsible for awarding honors at Cannes Lions. If there truly are billions of potential entries by then, they will surely need AI assistance themselves.
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