TL;DR
- The death of cookies presents challenges for the industry, but deep learning algorithms can still deliver strong performance by leveraging other signals and data.
- Understanding the data you’re using to create or fine tune AI models and processes is very important, so owning proprietary data is inevitably a huge advantage.
- AI will drive inefficiencies from the advertising process from the creative to analysis of campaign performance but the technologists says this won’t lead to a loss of jobs.
READ MORE: Nvidia on How AI Will Transform Adland in 2024 (Little Black Book)
Brands and agencies are excited about the potential of AI to bring mass personalization to advertising campaigns, but will need the assistance of experts to help them make the most of their data.
“If you consider that large agencies, media companies and holding companies [own] a huge amount of proprietary data about markets, audiences and campaign history [it is] going to enable them to create very powerful AI models,” said Jamie Allan, director of business development, global agencies and advertising at chip maker NVIDIA.
After a year of pilots and tentative AI activity in the world of advertising, Allan said that in 2024 we will see agencies asking the question, “How do you connect the power of generative AI with the power of data?”
Speaking with Little Black Book, Allan said that 2024 is “the year of platform and production,” telling LBB’s Ben Conway that it’s “true table stakes” for every enterprise in the world.
“It needs to not be the product anymore,” said Allan. “AI isn’t ‘the thing’ — it’s how AI helps us create new things.”
WPP, Publicis, Dentsu, Omnicon and Media Monks are among agency groups investing in AI trained on centralized pools of data to build mass targeted ad strategies for the post-cookie era.
“The idea of personalization-at-scale, from content production, and using proprietary data to create privacy-first personalization that can bring an era of a more attractive, dynamic one-to-one advertising,” Allan said. “Many years of research have shown that it can drive better brand engagement and growth, and improve return on ad spend.”
It is in NVIDIA’s interest to be talking about this since its chips are being sold into agency groups to supercharge the crunching of data.
“Understanding the data you’re using to create or fine tune AI models and processes is very important, so having your own proprietary data is inevitably a huge advantage,” he said.
“The quicker the business models can be adapted to the impact of AI, the more successful companies will be as well,” added Allan. “That’s something agencies have the opportunity to help guide brands on, once they become experts in that business transformation.”
He insisted that GenAI is not about the generation of content, but the generation of intelligence. “The quality of that intelligence is based on the data, the sources and the teams building those models and pipelines,” he said.
“If you are generating and owning data, then you should own the intelligence that that data is going to produce as well. And you should have the capability to generate that intelligence.”
Marla Kaplowitz, CEO of agency advocacy group 4As, recently stated, “GenAI is here to stay, leaving the advertising industry with a stark choice: adapt or become irrelevant.”
As 4As SVP of creative technologies and innovation Jeremy Lockhorn wrote in Fast Company, “agencies must embrace the opportunity to transform their revenue model.”
READ MORE: Thanks to generative AI, advertising’s business models will be reinvented (Fast Company)
Next in Media talked with Cognitiv CEO Jeremy Fain about what ad industry execs really need to understand about the difference between LLMs, deep learning and Computer Vision.
According to Fain, deep learning is a powerful tool in performance advertising, allowing for more efficient and effective targeting of impressions.
“Transparency and customization are key factors in successful media buying, and deep learning can provide insights and analytics to support these efforts,” Fain says.
His company applies AI, in the form of deep learning applications and technologies, to predict consumer behavior and self-drive full-funnel marketing performance at scale.
“If you rely on third-party cookies to message your customers, you could be missing out an 80% of the people you want to reach,” Fain said.
READ MORE: So you’ve been pretending to understand AI (Next in Media)
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AI will drive inefficiencies from the advertising process from the creative to analysis of campaign performance but the technologists says this won’t lead to a loss of jobs.
Allan said, “Jobs will be augmented and supercharged, especially in the creative side. The best in the industry are looking at these tools and setting out very flexible strategies about their creative pipelines — how they can integrate multiple tools and not be set in a single creative process.”
Fain said, “I think the roles will change but I don’t think that the number of people employed at agencies will necessarily materially change over the long term.
A recent Goldman Sachs study suggests that, in the next 10 years, most jobs will be complemented by AI, not substituted by it.
“If we let it, and get it right, we can use generative AI to tell more compelling stories, connect with audiences on a deeper level, and usher in a new era of advertising that is both effective and meaningful,” said Lockhorn.
