Measured, the AI-powered marketing effectiveness platform, released new research showing that incremental revenue and orders for brands grew after Google rolled out its AI Overviews feature broadly in September 2025. The analysis, based on 139 brands, found that median incremental revenue increased 3.4% and median incremental orders increased 3.2% while ad spend remained essentially flat. The findings challenge the assumption that AI-generated search results weaken traditional search as a performance channel.

The disconnect between platform reporting and incrementality measurement is central to the analysis. In an AI-shaped search environment, traditional metrics such as click-through rate may no longer tell the full story. AI Overviews is quite effective at answering informational queries directly, but those queries are often from lower-intent users who were less likely to convert in the first place. The remaining clicks may come from shoppers who are further along in the purchase journey.

"Many marketers spent the back half of 2025 worried that Google’s AI Overviews would erode search effectiveness," said Trevor Testwuide, CEO and co-founder of Measured. "What our data shows is that the channel didn’t weaken search; it concentrated it. The clicks that went away were the ones that were never going to convert anyway. The advertisers who watched incrementality instead of click-through rate saw that clearly. They kept investing and they came out ahead."

Omnichannel brands that use digital ads to drive in store sales stood out in the analysis. Among brands that also measure the incremental impact of paid media on retail store sales, median retail incremental revenue grew 43.7% and incremental orders grew 22.5%. Incremental return on ad spend (iROAS) for this subset rose from $1.35 to $1.47 across three consecutive months in the first quarter of 2026, pointing to sustained performance rather than a seasonal blip. These gains were not driven by cuts in ad spend, as median spend among the omnichannel subset grew 38% after the launch of AI Overviews.

Performance Metrics Overview

The following table summarizes the key performance metrics observed across the analyzed brands:

The report suggests that brands that continued to invest in Google ads and paid search campaigns through the AI Overviews rollout were better positioned to capture expanded search demand. For omnichannel advertisers in particular, maintaining coverage across purchase-intent queries helped convert search activity into incremental revenue and orders.

Google is currently negotiating with publishers to allow the use of their content for training its artificial intelligence models as part of a new pilot program. The initiative represents a significant effort by the tech giant to secure the necessary intellectual property rights to advance its AI capabilities. The negotiations are characterized by a firm stance from Google as it seeks to establish agreements that will facilitate the use of published material in machine learning processes.

The pilot program focuses on addressing the legal and ethical considerations surrounding the use of copyrighted material in AI training. By engaging directly with publishers, Google aims to create a framework for content licensing that could set a precedent for future industry practices. The discussions are critical as they involve the potential commodification of journalistic and creative works in the digital age.

Key Aspects of the Negotiations

The negotiations involve several critical components that both parties must consider:

• Licensing Terms: Establishing clear terms under which content can be used for AI training.
• Compensation: Determining financial or other forms of compensation for publishers.
• Scope of Use: Defining the extent to which the content can be utilized by Google's AI models.

The outcome of these negotiations could have far-reaching implications for the relationship between technology companies and content creators. As AI models require vast amounts of data to function effectively, securing legal access to high-quality content is becoming increasingly important for companies like Google.

The pilot program serves as a test case for how these complex issues might be resolved on a larger scale. It reflects the broader industry trend where AI developers are seeking to legitimize their data sourcing methods amidst growing scrutiny over copyright infringement and data privacy.