As 80% of U.S. ad spending is expected to flow through AI-powered platforms by 2028, marketers must work harder to preserve their autonomy.
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For all of the hype and consternation that artificial intelligence has wrought, it’s important to remember that it is still very young.Still, the marketing industry is becoming more and more reliant on the nascent technology to create efficiencies, solve problems and keep up with the digital world, particularly when it comes to media.
More than 70% of global ad spending and 80% of U.S. ad spending will flow through self-serve advertising platforms in which AI “materially influences” media buying, costs and outcomes by 2028, according to recent Gartner research. As a result, marketers would do well to be a little more discriminating about the information that comes out of self-serve ad platforms, said Eric Schmitt, vice president analyst in the Gartner Marketing practice.
“I think one has to be very cautious right now about turning over too much autonomy to these systems,” Schmitt said. “You wouldn’t give your 13 year old your credit card, send them to the grocery store and tell them to make good buying decisions. [Similarly,] you don’t want to give these ad platforms unfettered access to your media budget without a human in the loop.”
The AI was created in service of the platform, rather than the buyer, Schmitt explained. When the two competing objectives meet — maximizing price for the platform and minimizing cost for the buyer — it’s a no-brainer to see which the AI will express bias toward.
“It’s kind of unsurprising that a lot of the AI wizard recommendations that I see surfacing in these user interfaces start with, ‘You should spend more with us,’” Schmitt said. “At the end of the day, the core mission for these algorithms is to generate the numbers necessary for the platform provider to hit its quarterly revenue and profit results.”
Limiting variables with AI
Adding to the AI challenge is the fact that the platforms “don’t often play nice with each other,” Schmitt said. That means marketers still have to deal with the age-old conundrums of multichannel measurement and interoperability. Marketers need to be thoughtful when deciding how deeply to engage with AI tools on self-service platforms. They need a clear idea of their business objectives and which media will achieve them.
“Ask yourself: ‘What’s the overall role of the media relative to what I’m trying to accomplish?’” Schmitt said. “Don’t let the shiny objects and glitz of AI distract you from [investigating] the core physics of the platform.”
In addition to the traditional media questions about audience size and usage, marketers should evaluate whether the AI platform allows them to map how the money they’re spending ties directly to the desired outcomes. That may mean focusing on the few over the many, Schmitt said.
“Part of the puzzle is limiting the number of variables,” Schmitt said. Google, Meta and Amazon capture over half of overall paid media spending in the U.S., andare edging toward 60%of ad spend globally, excluding China.
“So, you want to be really looking at those platforms,” Schmitt said.
It also wouldn’t hurt to bring in other stakeholders to assess the efficacy of AI media-buying platforms, such as executives from finance departments.
“Use this as an opportunity to find common ground with your own internal stakeholders and make sure that your strategy is in line with theirs, as much as possible, so you can have consensus on the risk versus reward of these decisions,” Schmitt said.
Approach with caution
For all of these areas of concern, AI remains a powerful tool as marketers contend with more complex questions and look to create more effective, personalized advertising.
“As a user of the software, you’ve got to harness the capabilities that they’re building in,” Schmitt said. “But you don’t want to get so far over your skis that you say, ‘I can automate this whole thing. I don’t need a media planner anymore.’ Or, ‘Here’s a turnkey media plan that can run across all platforms.’ That’s getting into science fiction for me.”
The good news is, one doesn’t need to be an expert to begin using AI. Approaching the technology with a degree of caution is paramount regardless of skill level.
“You don’t need a tech background to start to troubleshoot or understand what’s happening,” Schmitt said. “You can take more junior people or repurpose existing staff and put them in front of these consoles. Even if they have never done a regression analysis or put together a campaign brief in their lives, they can now do that. And that’s great… until it’s not.”
That’s why experienced, attentive oversight is necessary, including from independent measurement providers — particularly in these developmental years.
“You have to play the [AI] game,” Schmitt said. “[But] judge the performance and outcomes of the campaigns through a lens that’s maybe a little different from the fox in the henhouse reporting that you will get from the individual platforms.”
