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How ads will integrate into AI-driven search and other questions you might have about generative AI

Companies like Google and Microsoft are racing to incorporate generative AI into their search engines, while Grammarly and Shopify are using it to round out their offerings.

As this transformation takes place, marketers are asking themselves how they can use AI well and responsibly. We asked our analysts to weigh in on the tech.

1. How will ads work within AI-driven search?

It’s not hard to imagine how ads can integrate into Bing’s AI search based on how it works right now, said Insider Intelligence senior analyst Gadjo Sevilla on a recent episode of our “Behind the Numbers: The Daily” podcast.

“You put in keywords and it generates a response based on the AI. So you can do the same either with links, ads, or even video content from within that search page.”

But pricing these ad units may be a different story.

“This is going to be a tough one to pencil out for tech companies running these programs,” said our analyst Jacob Bourne. “AI has a reputation for having very high computing costs, and we might see that ad revenue doesn’t suffice to pay for things. It might not quite do the trick in terms of generating revenue.”

It should be noted that AI-driven search may make users less likely to click on ads, since the information will be presented directly in the search results.

2. Does the rise of AI-generated content mean more brand safety issues for marketers?

In short, yes.

“I think this is going to be a massive problem,” said Bourne, citing the threats marketers face from both inside and outside the company.

Internally, AI-generated content will need to be vetted to ensure that it is consistent with branding and doesn’t pose any brand safety issues. Externally, marketers should be on the lookout for AI-generated spam content that could be used to impersonate brands.

Given generative AI’s unpredictable nature, there’s also the possibility that ads may appear alongside problematic content or content that brands don’t want to be associated with.

3. Is there a way of measuring the level of AI in a product or service?

Not right now, said Sevilla.

“I think transparency is one of the bigger issues surrounding generative AI. We’ve seen companies employ it without spelling it out, [getting] into trouble, and then [saying] later on that it was an experiment,” he said. Cnet, for example, came under scrutiny for using AI to write articles that were riddled with errors.

Even if a system emerges, it’s going to be difficult for it to measure all the ways that generative AI is used, said Bourne.

Ultimately, companies should be extra careful and responsible with how they use AI, he said, citing consumer concerns over chatbots going rogue and “love bombing” users.

4. What are some of the best business cases for generative AI today?

Right now, it’s a successful assistive tool, said Sevilla.

“You can have an AI that listens in on meetings and takes down notes and proactively schedules agendas,” he said. “Or a research bot that could sift through data to determine redundant sources and grade the quality of the content.”

Bourne urges companies to look at generative AI as a tool for creative inspiration rather than just a shortcut.

“I think there’s a risk of quality declining as a result of using it just for time-saving versus looking at how we can be more creative in our work using these tools for collaboration, instead of as a replacement for certain functions.”

Listen to the full podcast.


This was originally featured in the eMarketer Daily newsletter. For more retail insights, statistics, and trends, subscribe here.