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Home » News » Google’s Shashi Thakur Addresses Concerns Over AI Search Impact on Traffic and Ads

Google’s Shashi Thakur Addresses Concerns Over AI Search Impact on Traffic and Ads


In a recent interview with Marketing Brew, Google’s VP/GM of Advertising, Shashi Thakur, discussed user interactions with links in AI Overviews, amidst ongoing criticism regarding the quality of Search results and concerns from brands and content creators about reduced organic search traffic.

User Interaction with AI Links

Thakur highlighted that despite the criticisms, users are actively clicking on links embedded within AI-generated answers. Read here.

However, he did not provide specific statistics or research to substantiate this claim. Thakur acknowledged publishers’ worries about potentially receiving fewer clicks from Google Search results, which could adversely impact their ad revenue. He reassured that AI answers include links and that the diversity of publishers being clicked on has increased.

Publisher Concerns and Traffic Monetization

The primary concern for publishers revolves around traffic and its monetization. Thakur pointed out that AI answers drive users to explore further, leading to an increase in clicks on embedded links. This shift towards AI Overviews, however, moved the focus from traditional display ads on publisher sites to interactions within AI-generated content. This transition has been criticized because publishers prioritize traffic that can be monetized through visibility and engagement.

Commercial Queries and Advertising Opportunities

Thakur also touched on the dynamics of AI search in commercial queries. He emphasized that users still need to click through to complete actions, providing opportunities for advertisements that complement AI answers. This engagement is crucial for maintaining the efficacy of ads within AI-generated responses.

Microsoft Bing’s Perspective

In contrast, Fabrice Canel from Microsoft Bing suggested that AI search would result in fewer but more “qualified clicks.” This approach is predicated on the idea that AI answers should streamline the user journey, reducing the number of searches needed to accomplish tasks.


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