Google: AI Overviews Earn Like Search

Google has stated that its AI Overviews are producing advertising revenue on par with traditional search results. This revelation could have a significant impact on digital marketing strategies moving forward.

The tech giant is not only standing by this claim but is also in the process of rolling out AI Overview advertising on a global scale. This suggests that AI-powered search experiences are set to become a more central part of the platform.

For marketers, this shift means it’s crucial to adjust to new patterns in user behaviour. As queries become more complex and users increasingly rely on AI-generated summaries, the way ads are placed and interacted with is changing.

To keep up, advertisers will need to rethink how they target audiences and create campaigns that align with evolving search experiences. Understanding how AI Overviews function and influence user engagement could become key to staying competitive in the online space.

Google has stated that search results featuring AI Overviews are generating the same level of advertising revenue as standard search listings.

This announcement came during the Google Marketing Live event, where the company also shared its plans to roll out AI Overview adverts to desktop users and more English-speaking regions.

If this proves to be accurate, it could significantly influence how marketers approach Google’s AI-driven direction for the future.

However, the claim does invite scrutiny, particularly around how Google is measuring these results and what it might mean for ongoing ad campaigns.

For marketers, it’s important to dig deeper into these statements and understand what they could signal for the evolving landscape of search-based advertising.

AI Overviews Reaches Massive Scale

Google first introduced AI Overviews on mobile devices in the United States last year. Since then, the feature has seen a rapid global expansion, now providing AI-generated responses to users in over 200 countries.

During a press session, Shashi Thakur, Google’s Vice President and General Manager of Advertising, shared that the feature is reaching 1.5 billion users every month.

Thakur, who oversees advertising across a range of Google platforms including Search, Discover, Image Search, Lens and Maps, said that user feedback on AI Overviews has been positive so far.

The global rollout, including the recent announcement of its launch on desktop, highlights Google’s confidence in the feature’s widespread adoption and its potential to perform well commercially.

Explaining the feature’s growing impact, Thakur mentioned that users are now asking more questions, including commercial ones, thanks to AI Overviews. This increase in engagement suggests that the tool is not only popular but also helping to drive advertising growth.

Google’s Broader Vision For Search Evolution

Google’s strategy with AI Overviews marks a major shift in how the company views the future of search. According to Shashi Thakur, the aim is to expand the ways people can engage with search engines.

He explained that Google sees search as a tool to help users express a wider range of curiosities. At the moment, only a small portion of those curiosities are actually entered into search. As the technology improves, Google believes users will feel more empowered to ask broader and more complex questions.

This thinking is at the heart of Google’s move towards AI-driven search results. The goal is to provide smarter, more helpful responses that go beyond simple keyword matches and instead address more detailed and nuanced queries.

How Google Measures AI Overview Monetization

Google’s claims about revenue from AI Overviews are based on data from controlled experiments. The company uses A/B testing, comparing identical search terms shown with and without the AI Overview feature.

This approach involves displaying the AI feature to a selected group of users while withholding it from others. By doing so, Google can measure the difference in advertising revenue between the two groups.

Shashi Thakur explained during a press briefing that when they say AI Overviews generate revenue at the same rate, it means that if the same search queries were run without the AI feature, the revenue results would be similar.

The company focuses on the overall business value rather than specific performance indicators like click-through rates. According to Google, their findings represent trends across a large volume of searches rather than individual examples.

For advertisers, this may offer reassurance that AI Overviews don’t appear to reduce the impact of search advertising. However, it remains to be seen how changes in user behaviour over time might affect these outcomes.

Strategic Approach To AI Overview Advertising

Google has stated that adverts appearing within AI Overviews are subject to the same quality standards as traditional search ads. The company emphasises that all advertising must enhance the user experience and be clearly labelled as sponsored content.

Advertisers are given three placement options when it comes to AI Overview ads. These can appear above the AI-generated response, below it, or even be embedded directly within the answer itself. This flexibility allows marketers to tailor how their promotions align with AI-driven search content.

According to Google, the increasing complexity of user journeys is shaping their advertising strategy. Shashi Thakur highlighted that people now find inspiration to begin their commercial journeys at many different points, making it essential to understand and respond to that complexity.

A key part of this approach is recognising “faceted” searches—complex queries that often include several smaller questions. Some of these sub-questions may indicate a commercial interest, which creates natural opportunities for relevant adverts to be shown.

Thakur gave an example to illustrate this: a user searching for airline rules about travelling with pets might also need pet carriers or other travel gear. This opens the door to commercial responses embedded within an otherwise informational query.

To enable this, Google uses advanced classifiers to detect different types of commercial intent. These include shopping-related searches, travel plans, and insurance questions. The system then uses this information to match users with suitable adverts.

Thakur reiterated that maintaining quality is key: adverts must be both relevant and consistent with the overall experience. He explained that ads shown in this context actually improve the value of the AI-generated responses for some users.

According to Google, users have responded positively to the presence of these integrated adverts, suggesting that they don’t interfere with satisfaction levels during searches.

This acceptance appears central to Google’s plan, as they aim to roll out AI Overview adverts across more markets and platforms in the near future.

Implications For Digital Marketers

Google’s claim of revenue parity is intended to ease advertiser concerns around how AI might affect the performance of search advertising. By suggesting that ad revenue remains consistent, even with AI Overviews, the company hopes to reassure marketers.

Shashi Thakur addressed a central question many advertisers are now raising. He acknowledged that as search continues to evolve in new and exciting ways, businesses are eager to understand how they can continue connecting with customers within this changing landscape.

According to Thakur, more than 80% of Google’s advertisers are already using some form of AI-based advertising tools. This high adoption rate suggests that the industry is largely prepared for deeper AI integration in digital marketing.

However, as AI-powered search becomes more sophisticated, advertisers may need to adjust their strategies. Users are increasingly entering more detailed, multi-layered queries that traditional keyword-based methods may struggle to accommodate.

In response, Google is ramping up automation with tools like the newly introduced “AI Max for search.” Early trials of this feature have shown encouraging outcomes. Advertisers testing AI Max have seen an average 27% rise in conversions, while still hitting similar ROI goals.

Thakur explained that AI Max was developed with changing user behaviour in mind. As users shift toward more complex and conversational searches, advertisers have also made it clear they value transparency and control—features that AI Max aims to preserve.

Despite its automated nature, the tool includes elements familiar to marketers, such as keyword-level reporting and campaign controls. These allow advertisers to retain insight and influence over their campaigns, even when automation is in use.

Google’s push for automation highlights a wider issue: as search behaviour shifts toward more natural language and layered queries, it becomes more difficult to align ads manually with user intent.

As a result, relying solely on manual keyword strategies may become increasingly ineffective. Advertisers will need to embrace AI-driven tools to keep pace with the ongoing evolution of search behaviour.

AI Mode Expansion Creates New Opportunities

In addition to AI Overviews, Google is now experimenting with adverts in its new feature called AI Mode. This tool allows for fully conversational search experiences, giving users a more natural way to interact with search results.

Initial findings show that users engaging with AI Mode tend to ask much longer questions—sometimes up to twice the length of typical search queries. These extended, conversation-style queries offer more context, which can help in identifying the user’s commercial intent more accurately.

Because of this added detail, advertisers could benefit from more targeted ad placements, as the richer information allows for a clearer understanding of user needs. This may lead to better alignment between adverts and user intent.

Google is also working to ensure that the quality of adverts shown in AI Mode remains consistent with those in AI Overviews. Drawing on its previous experience, the company is focusing on maintaining high standards in both relevance and user experience.