Generative AI Pushes Deeper into the Consumer’s Online Experience

The ad tech industry is all in for the generative AI hype, but an Intango survey reveals that consumers’ opinions about using generative AI for advertising are a mixed bag. 

Generative AI is rapidly infiltrating and, in many cases, dominating the consumer’s online experience. Is this enhancing the consumer experience? Will publishers benefit from greater engagement with ads on their sites? Or are we simply drinking our own KoolAid, like we did in the data-driven days of Web 2.0? 

Research shows that consumers might not be as keen to see AI-generated ads as many assume.

The Generative AI Ad Funnel

Search is the first place people go when they have a question or are interested in a product, and for many publishers, it can represent up to 40% of the users who arrive on their site. However, Google SGE allows consumers to skip that step and get quick answers without bothering them by visiting the site that produced the content. 

While Google SGE hurts publishers by cutting off a vital source of referral traffic, generative AI can, in theory, help them improve the monetization of users who find their way to their sites. Tools like,, and others allow for myriad combinations of ad copy and images using a range of data about the individual, prompting higher levels of engagement and, ultimately, CPMs.  

Personalization is Good for Consumers, Right?

Our industry believes the fact that generative AI algorithms can analyze vast amounts of data and generate ad content personalized to individual users is a good thing. But how do consumers feel about all of these AI-powered experiences?

New research shows that consumers have mixed opinions. Last Thursday, Intango released the results of a study designed to measure consumer perceptions of generative AI in advertising. The ad-tech company surveyed over 1,000 consumers in the US and found opinions divided on critical issues that the industry believes are beneficial.

Take using search history for ad personalization. Forty-three percent of respondents viewed this positively or somewhat positively, indicating an appreciation for more tailored advertising experiences. Yet, this enthusiasm is tempered by privacy considerations, with 37% expressing reservations about their search history used to shape ad content.

As tools like Soro and Google Performance Max proliferate, consumers are on the fence about all that personalization. When asked about their receptivity to AI-driven personalized ad content, 45% of participants acknowledged the benefits of such personalization, either finding it beneficial or somewhat beneficial for ensuring ad relevance. However, skepticism remains, as 27% /preferred non-AI personalized ads, highlighting the industry’s challenge in balancing technological advancement with consumer comfort and trust.

And while Google touts Search SGE, the survey revealed that 27% of consumers adjust their search behaviors with a shift toward these new platforms. A majority (51%) reported no change in their use of traditional search engines. According to Intango, this indicates a gradual but noticeable shift in consumer search habits influenced by AI innovations. 

These findings confirm earlier research by Publicis Media and Yahoo!, which served 1,200 consumers about their attitudes towards AI-generated content. According to that poll, 72% of consumers found that AI makes distinguishing between authentic and fake content difficult. 

The Importance of Navigating Carefully

“It is evident that while there’s an appreciation for and curiosity about the enhanced experiences that AI-driven personalization can offer, consumers do have privacy concerns,” Uri Lichter, CEO of Intango, said in a press release. “It’s crucial for us in the ad tech industry to navigate these concerns thoughtfully. We need to take a careful approach when advancing AI in search to ensure we are respecting consumer privacy while delivering the personalized experiences that many users value.”

Navigating those concerns can be tough for our industry because we tend to get excited about the hype. The mid-aughts were all about data-driven advertising and capturing the “data exhaust” consumers generate as they go about their digital lives. We tracked their every move, packaging up signals into audience segments sold at scale, leading to what Harvard Business School professor Shoshana Zuboff calls surveillance capitalism.

It was a heady time within the industry, with ad-tech companies promising highly personalized advertising that makes the whole online experience better for the consumer. However, they didn’t quite agree. Blowback came from the GDPR, CCPA, and an increasingly complex regulatory environment. 

There’s no doubt that personalized advertising increases relevance and efficiency and promotes discovery. But consumers have made it clear that they’re uncomfortable with companies knowing so much about their online behavior and, worse, using it to manipulate their behavior to get them to buy things they don’t need or want.

We learned some valuable lessons in Web 2.0. This research reminds us that we need to apply those lessons as we dive into generative AI.

Besides, we might be getting our hopes up that generative AI will be the panacea for increased ad engagement. In his book Filterworld, Kyle Chayka warns, “With new technology, the miraculous quickly becomes mundane, any glitch in its function is felt as bothersome, and finally it becomes ignorable, the miracle forsaken.” In other words, the video ads created by Soro may seem super cool at first, but if we see them enough, we’ll grow bored.

How Generative AI Can Help AdOps

This is not to say that generative AI won’t have a huge and positive impact on publisher revenues because it will. Last week, NBCUniversal announced at One24 that it is testing generative AI to analyze TV and social content to better understand the emotions and motivations felt by consumers. Advertisers can then use that insight to target audiences for ads, increasing ad revenue for NBCUniversal content. Early tests show that this insight can improve performance by as much as 49%.

The soon-to-be-released AdMonsters Publisher Pulse found that AdOps teams effectively use generative AI to improve monetization in myriad ways, such as implementing infinite feedback loops that collect, analyze, and optimize campaigns automatically and continuously.