Google now injects hyper-personalized ads into third party AI chats

As it stands to potentially lose ad revenue after being ruled a monopoly, and also to maintain an edge in the digital ad space as generative AI use soars, Google is purportedly now injecting ads into third party chatbot conversations.

It’s not a surprising move, particularly given Google’s antitrust loss that could eventually lead to the breakup of its ad business (although there are likely years of appeals to come before any tangible changes). The tech giant is also in fierce competition with the likes of OpenAI, Perplexity, Meta, Microsoft, Salesforce, and a slew of others to get enterprise users to adopt its genAI platforms.

“Google knows its long-dominant search funnel is leaking,” said Julie Geller, principal research director at Info-Tech Research Group. “If conversational AI becomes the way people discover, decide, and buy, Google needs a revenue engine ready before regulators or rivals box it out.”

More than a money move

According to reports, the Google AdSense network expanded to include chatbot conversations earlier this year, after it tested the capability last year. Particularly, according to anonymous sources, it is working with AI search startups iAsk and Liner.

The move comes as Google grapples with the fallout of not just one, but two, antitrust trials in which it was found guilty of establishing “monopoly power.” Most recently, in April, a federal judge in Virginia ruled that the company monopolized two online advertising markets: publisher ad servers and the ad exchanges that sit between buyers and sellers. Google reportedly earned nearly $265 billion in 2024 alone through ad placement and sales.

Incorporating ads into generative AI is a “risky move at a fragile moment,” noted Ria Delamere, chief technology and product officer at Traject Data. “This isn’t just about making money. It’s about trying to hold onto ground as Google faces pressure from AI-native competitors and antitrust regulators.”

An opportunity for hyper-personalization

Of course, Google isn’t the first to do this. Meta, for one, shows ads in “private” messenger chats, David B. Wright, president and chief marketing officer at W3 Group Marketing, pointed out.

“Google and other companies inserting ads in AI chatbots are just jumping into the next available space to place ads,” he said.

Geller pointed out that, in 2022, company leaders acknowledged that about 40% of Gen Z in the US were turning to TikTok or Instagram, not Google, for local recommendations on where to eat or shop, and that behavior has only accelerated since. Incorporating ads into generative AI sets the stage for “hyper-local, persona-level targeting” which could  pull advertisers back from social platforms and keep both discovery and dollars inside Google’s walls, she said.

Enterprises will be able to deliver more relevant ads “at the right time to the right person,” Wright agreed. Consider conversing with an AI chatbot as a very long-tail search, he said: Ad servers can take the data from the conversation and use it to craft hyper-targeted ads.

“In an ideal world, we’d only see the ads we want to see when we’d want to see them: when we’re at the right stage of a buying decision for something we want to buy,” he said. “This could be a step closer to that.”

Preserving trust will be paramount moving forward

Experts emphasize that trust is imperative to all this. Notably, it hinges on “knowing when money changes the message,” said Geller. If users suspect an answer is ranked by revenue over relevance, “confidence tanks,” and they may migrate to more “neutral” assistants.

Google will need to flag sponsored content in real-time, explain why it surfaced the ads it did, and prove that organic answers aren’t “quietly demoted,” she said. “Anything less invites skepticism and churn.”

Delamere agreed that when ads start showing up as part of an “answer,” it gets harder to tell where information ends and influence begins. When AI is driving decisions, transparency and explainability aren’t an option, she said.

“This may help Google in the short term, but credibility is hard to earn and easy to lose,” Delamere emphasized.

From a user interface perspective, if ads distract or cause delays, consumers won’t go near the app, noted Melissa Copeland of Blue Orbit Consulting. “Consumers may try it, but if they don’t get the efficient and effective answer they are looking for, they will abandon the channel or brand.”

Meanwhile, when it comes to privacy, Geller pointed out that chat transcripts are stored and, at times, reviewed by humans, creating a “durable record of anything sensitive a user blurts out.”

“While Google offers opt-outs and deletion tools, they’re far from intuitive,” she said, emphasizing that enterprises must offer secure contract-level clarity on retention windows, human-review policies, and encryption standards, and should also insist on audit rights to verify compliance.

Look beyond a single-vendor strategy

This type of capability could help companies offer chatbot functionality at a lower cost, and potentially surface new insights about customers, noted Neil Chilson, head of AI policy with the Abundance Institute.

Like all ad media, he said, when considering the volume and type of ads, companies will need to balance short-time incentives to monetize and long- term financial incentives to keep customers coming back.

“Google is good at helping companies evaluate those trade offs in other advertising channels; it will be interesting to see how that expertise translates to this new area,” said Chilson.

Info-Tech’s Geller pointed out that the search and discovery landscape is evolving too quickly for a single-vendor strategy. She advised enterprise leaders to stay agile, demand full transparency around data use and monetization, and keep an eye on how AI-driven personalization opens new micro-market opportunities.

It’s also important to build flexibility into customer experience and marketing roadmaps, as ads are “only the opening salvo,” she noted. Further, companies should watch for new revenue models from app providers, such as subscription tiers or usage fees, and potentially embrace the benefits of hyper-local targeting. At the same time, she said, “keep exit routes open and your data governance questions sharp.”