Advertisers are sounding the alarm this week over the performance of Google’s AI Max for Search campaigns. Launched in May 2025 with promises of delivering more conversions, the tool is reportedly failing to meet expectations.
According to new data shared by marketing professionals the AI-powered system is significantly underperforming compared to traditional ad-targeting methods. Some advertisers cite cost-per-conversion rates up to 90% higher than older match types.
Such results challenge Google’s claims of AI efficiency and create a potential setback in its race against rivals like Amazon and Meta to automate digital advertising. Google has not yet commented on the reports.
From Promised Gains to Performance Pains
Six months after its debut, Google’s AI-powered advertising tool is facing a wave of criticism from the very users it was designed to help. When Google rolled out AI Max for Search campaigns in May, it positioned the feature as a powerful, one-click upgrade to enhance ad relevance and drive growth.
Google’s internal data suggested that advertisers could see a 14% increase in conversions or conversion value at a similar cost, a compelling proposition in a competitive market.
Early testimonials supported this optimistic narrative. Google highlighted success stories from major brands like L’Oréal, whose CMO for Chile, Nicolás Moya, stated, “AI Max not only allowed us to pioneer the use of AI in Search — it also propelled us into new markets, reaching untapped audiences with lower costs.”
Another early tester, Australian utility service MyConnect, reported seeing 16% more leads at a 13% lower cost-per-acquisition. These initial reports, combined with the industry-wide excitement for generative AI, painted a picture of a sophisticated tool capable of unlocking new efficiencies for businesses of all sizes.
As the tool has become more widely adopted, however, a starkly different picture is emerging from the field.
Advertisers Share Disappointing Data
For many digital marketers, the promise of AI-driven efficiency has given way to frustration and significantly higher costs.
A recent discussion initiated by advertiser Xavier Mantica on LinkedIn has become a focal point for these concerns. After four months of rigorous testing, Mantica shared data showing that “AI Max campaigns are showing 90% higher cost per conversion than phrase match.”
His detailed breakdown revealed AI Max was the most expensive match type by a significant margin. Its cost per conversion was a staggering $100.37, compared to just $43.97 for phrase match and $52.69 for exact match.
Even close variants of phrase match, at $97.67, performed better than the new AI system. Far from optimizing ad spend, the data suggests the tool was actively eroding campaign profitability.
Mantica’s experience is not an isolated incident. Analyst Mike Ryan replied to the thread, stating he “looked at over 250 campaigns and found it’s also the worst match type by the numbers.”
Others in the industry, including analyst Andrew Goodman, echoed the sentiment, with Goodman expressing his skepticism by noting, “I’ll wait to be proven wrong by any credible case study (that doesn’t involve just luck or a very poorly-run account getting a lift).”
This growing chorus of negative feedback points to a systemic issue, fueling a wider distrust of Google’s automated recommendations.
Many omments indicate that the poor performance of AI Max is causing advertisers to question the value of Google’s entire suite of automated tools.
An Unsettling Silence in the AI Ad Race
In the high-stakes battle for advertising dollars, real-world performance is the ultimate metric. Google’s current struggles with AI Max are particularly notable given the fierce competition in the ad tech space. T
he push toward full automation is a strategic imperative for tech giants. Amazon recently launched its own powerful agentic AI assistant to help its millions of sellers create entire ad campaigns from simple conversations, while Meta has been vocal about its goal to fully automate its ad platform.
For Google, this incident places the company on the back foot. A public failure to deliver on performance promises could damage the advertiser trust that is the bedrock of its multi-billion dollar advertising empire.
Compounding the issue is Google’s apparent silence. As of this report, the company has not issued a public statement addressing the widespread complaints about AI Max’s underperformance, leaving frustrated advertisers without answers or solutions.
This lack of response is happening just as Google has been making other moves to increase transparency. The company recently announced it would provide more detailed ‘channel performance’ reporting for its Performance Max (PMax) campaigns, a move seen as a response to long-standing criticism of its AI tools being opaque ‘black boxes’.
While that update addresses a different product, it signals an awareness within Google of the need for greater advertiser control and insight. For the marketers currently paying a premium for subpar results from AI Max, a similar level of transparency—and a functional, cost-effective product—cannot come soon enough.
