How AI is impacting search advertising’s growth

“Bing is making a massive play with their investments in OpenAI and ChatGPT, while TikTok and Instagram are the go-to search engines for Gen Z,” Hamilton said. “It could take some time to assess the full effect of these shifting user behaviors, but the impacts could be landscape-altering.”

Search advertising was steadily increasing even before the pandemic, but the digital acceleration coming out of 2020 has led to exponential growth across search engine and marketplace platforms. In 2023, global ad spending in search advertising will reach about $279.3 billion, up from $251.7 billion in 2022, according to Statista Market Insights. Most of that will come from the U.S., which will account for $118.2 billion this year.

Amid this growth, search is shifting from consumers asking for information to expecting platforms to know what they need. Search engines like Google can anticipate what people need to know before they even have to ask, so marketers have to learn about consumer behavior in order to tailor their content accordingly. As Frisco Chau, global head of data and insights at IPG’s Huge, explained, AI can help refine contextual keywords and make the bidding process more cost-efficient.

“It allows us to design and think about the next experience and the next products and services,” Chau told Digiday. “Those signals that we have, in theory, allows us to push them through a search strategy in a much more holistic way — beyond everyone using keyword planner to understand where to get it.”

The result is a richer and wider library of different keywords, and, therefore, more contextual keyword possibilities. This also means pricing can become more cost-efficient on the advertising side, because there will be more keywords beyond the obvious ones in a given competitive category, Chau added. If everyone is bidding for a popular keyword, the reach becomes expensive — but AI can reveal the “less obvious and unknown” keywords for a similar audience type, Chau said.

“I’m selling shoes, and therefore I should go out to keywords around sports and activities and so forth. But you might find that actually, there’s something around parenting, like that is completely unobvious. But actually, if you went into those contextual issues, then it might be a different way of trying to try to approach the issue,” Chau said.

At agency Red Door Interactive, testing around AI and search has involved using tools for keyword research and analyzing articles. It’s been helpful, especially for discovery and research on complex topics, explained Ron Hadler, vp of data and innovation at the agency.

“We’re using it for topics we don’t understand,” Hadler said. “Your younger people and your middle people — helping them level up to somebody who’s a true expert. … So it is definitely a way to get folks who are operating at a low- or mid-level to operate above their punch weight.”

Hadler said the agency is treating AI as a companion, and that the technology has limitations. For one, there are privacy concerns on the client side regarding sensitive data being shared. Hadler said Red Door Interactive is testing AI in almost every department to “speed up and level up,” but there are policies in place about how to use it and when to be transparent, as well as to educate clients.

“Do not put client data into these platforms because you don’t know what they’re actually ingesting, saving and then being able to spit out to other folks,” Hadler added.

Hamilton at Good Apple similarly mentioned safety concerns in sharing sensitive data, especially in verticals like health care. The agency is also using AI capabilities across client services including proprietary bidding solutions, but it does not share client data with large language models like ChatGPT.

“We cannot rely on AI for copywriting or content generation beyond the ideation stage,” Hamilton said. “ChatGPT’s launch opened the generative AI floodgates, and every industry faces some form of AI disruption moving forward.”