Google's AI Max for Search campaigns deliver meh results, industry tests reveal

Google announced AI Max for Search campaigns on May 6, 2025, promising "14% more conversions or conversion value at a similar CPA/ROAS." However, early testing by advertising professionals reveals concerning patterns that challenge the technology giant's optimistic projections.

According to Ezra Sackett, Director of Paid Search at Monks, initial data from multiple client accounts shows "99% of impressions have 0 conversions" across approximately 30,000 search terms matching with AI Max features. The analysis, shared through professional networks, indicates that while the system generates extensive long-tail traffic, conversion performance remains problematic.

"We have a few clients dipping their toes into AI Max, and the results are... meh," Sackett stated in a detailed analysis posted on August 13, 2025. The findings reveal that 31% of search terms exceeded 25 characters in length, with the majority appearing as keywordless matches rather than traditional keyword-triggered advertisements.

The comprehensive suite of targeting and creative enhancements, introduced by Brian Burdick, Senior Director of Product Management at Google Ads, leverages artificial intelligence to expand search campaigns beyond traditional keyword matching. The platform promises to help advertisers "show up on more relevant searches" through broad match and keywordless technology that learns from existing keywords, creative assets, and URLs.

Technical implementation reveals automation challenges

AI Max for Search campaigns operates through three primary mechanisms. Search term matching expands keyword reach using broad match and keywordless technology to discover previously inaccessible queries. Text customization, formerly known as "automatically created assets," generates headlines and descriptions based on landing pages, advertisements, and keywords. Final URL expansion directs users to optimized website pages rather than specified destinations.

The system prioritizes keywords and keywordless matches similarly to existing Search and Performance Max campaigns. According to the Google announcement, "Google AI will learn from your current keywords, creative assets and URLs to help you show up on more relevant searches."

Testing data suggests significant discrepancies between promised and actual performance. While Google's internal studies indicate "14% more conversions or conversion value at a similar CPA/ROAS" for general adoption and "27% uplift" for campaigns primarily using exact and phrase keywords, independent testing reveals different outcomes.

Professional analysis indicates that "less than 1/2 of search terms show they are matched to a keyword," with the majority functioning as keywordless advertisements. This shift represents a fundamental change from traditional search advertising, where keyword relevance directly influenced ad delivery and performance measurement.

Case studies demonstrate mixed performance outcomes

L'Oréal Chile implemented AI Max across multiple markets, achieving "2X higher conversion rate at a 31% lower cost-per-conversion" through search term matching capabilities. Nicolás Moya, CMO of L'Oréal Chile, reported success "reaching untapped audiences with lower costs, higher conversions and more relevant ad experiences."

The beauty company specifically unlocked conversions from previously inaccessible queries such as "what is the best cream for facial dark spots?" by activating search term matching within AI Max configurations. L'Oréal's implementation demonstrates the technology's potential for discovery-based searches where users express intent through question-based queries.

MyConnect, an Australian utility connection service, achieved "16% more leads at a 13% lower cost-per-action" while already utilizing AI-powered features including target ROAS bidding and broad match keywords. The company observed "30% increase in conversions specifically from net-new queries," prompting expansion to additional Search campaigns.

Bec Oxnam, Head of Marketing at MyConnect, emphasized that "AI-powered creative and targeting enhancements in AI Max for Search campaigns, we were able to drive incremental high-quality leads by unlocking net-new searches and having AI build more relevant content to each user and their query."

Enhanced controls address advertiser concerns

Google introduced precision controls to address transparency concerns within automated advertising systems. Locations of interest enables geographical targeting at the ad group level based on user intent rather than physical location. Brand controls allow advertisers to specify brand associations or prevent advertisements from appearing alongside specific competitors.

A specialized URL parameter provides search term visibility across all match types, enabling real-time landing page optimization and detailed tracking as targeting expands beyond traditional parameters. The implementation addresses longstanding requests for campaign transparency that have characterized Performance Max and automated campaign discussions.

Reporting improvements include headlines and URLs within search terms reports, providing clearer customer journey visualization. Enhanced asset reports display performance against spend and conversion metrics rather than impression-based measurements. Advertisers can remove generated assets through asset removal controls or specify customer destinations through URL management features.

The platform also introduced asset optimization panels that generate text assets based on landing pages, advertisements, and keywords. According to Google's announcement, "our ability to generate assets that feature clear calls-to-action and unique selling points has improved."

Industry experts recommend cautious testing approach

Professional recommendations emphasize measured testing rather than wholesale adoption. Advertising specialists suggest limiting initial budget allocation to specific account segments while utilizing Google's recently introduced A/B testing tools for impact measurement.

"Don't throw all your budget into AI Max to start. Start with a segment of your account and scale up (or down) accordingly," Sackett advised in his analysis. The recommendation reflects broader industry caution regarding automated advertising systems that reduce advertiser control while promising improved performance.

Search term monitoring and negative keyword management become critical for AI Max implementations. Final URL expansion requires careful exclusion of inappropriate landing pages to prevent traffic direction to unsuitable website sections. Learning periods typically require 1-2 weeks before performance stabilization, with evaluation periods extending 4-6 weeks after learning completion.

Testing timelines acknowledge platform development cycles. "If you test it now and it doesn't work, test again later this year or in 2026," Sackett noted. "AI Max is one of the top priorities for Google and I anticipate several improvements to the product in the coming months."

Platform evolution mirrors Performance Max development

The AI Max rollout parallels Performance Max campaign introduction patterns from previous years. Early Performance Max implementations faced similar criticism regarding transparency and control limitations before subsequent feature enhancements addressed advertiser concerns.

Google's 2025 Performance Max updates included campaign-level negative keyword lists, increased search theme limits, and enhanced demographic targeting capabilities. These improvements suggest similar development trajectories for AI Max functionality.

Industry analysis indicates that "Google has been very clear on the direction things are headed, and I don't think avoiding AI Max is a viable option." The platform's strategic importance within Google's artificial intelligence advertising initiatives suggests continued development investment regardless of initial performance concerns.

The AI Max announcement preceded Google Marketing Live on May 21, 2025, where additional artificial intelligence features received introduction across Google's advertising ecosystem. The timing indicates AI Max's central role in Google's broader automation strategy.

Global rollout targets all advertiser segments

AI Max for Search campaigns entered global beta distribution during late May 2025, with availability expanding to all advertisers regardless of account size or spending levels. The democratization of artificial intelligence features represents Google's effort to standardize automation across its advertising platform.

Google Ads API v21, released on August 6, 2025, introduced technical support for AI Max through the ai_max_setting.enable_ai_max field. The API integration enables automated activation and management through third-party tools and custom implementations.

Developer documentation emphasizes that AI Max features operate exclusively when enabled by advertisers, maintaining conscious control over automation levels. The technical implementation requires explicit activation rather than default deployment, addressing concerns about unintended campaign modifications.

Google Ads Editor 2.10, released on July 8, 2025, incorporated AI Max toggle functionality within the desktop application. The offline editing capability enables bulk activation across multiple campaigns while maintaining detailed configuration controls.

The platform expansion coincides with broader artificial intelligence integration across Google's advertising properties. Search and Shopping advertisements will appear within AI Overviews, while AI-powered creative generation extends to additional campaign types beyond Performance Max implementations.

Timeline

• May 6, 2025: Google announces AI Max for Search campaigns with promises of 14% conversion improvements
• May 21, 2025: Google Marketing Live showcases AI Max alongside other artificial intelligence advertising features
• May 31, 2025: Google publishes comprehensive AI Max implementation guide
• July 8, 2025: Google Ads Editor 2.10 adds AI Max toggle functionality for desktop management
• August 6, 2025: Google Ads API v21 introduces technical AI Max support through developer tools
• August 13, 2025: Industry professionals share early testing results revealing conversion challenges

Summary

Who: Google announced AI Max for Search campaigns while advertising professionals including Ezra Sackett from Monks conducted independent testing to evaluate real-world performance against company projections.

What: AI Max for Search campaigns represent a comprehensive artificial intelligence suite featuring search term matching, text customization, and final URL expansion designed to expand advertiser reach beyond traditional keyword targeting while maintaining conversion performance.

When: Google announced the feature on May 6, 2025, with global beta rollout beginning later that month and early testing results emerging by August 13, 2025, revealing significant discrepancies between promised and actual performance metrics.

Where: The feature operates across Google's Search network with global availability to all advertisers, while testing data comes from multiple client accounts managed by advertising agencies and in-house marketing teams across various industries.

Why: Google introduced AI Max to help advertisers capture search opportunities beyond traditional keyword matching while leveraging artificial intelligence for creative optimization, though early results suggest the technology requires additional development to meet conversion performance expectations.

PPC Land explains

AI Max for Search Campaigns: Google's comprehensive artificial intelligence suite that enhances Search campaigns through automated targeting and creative optimization. The platform combines search term matching, text customization, and final URL expansion to help advertisers reach queries beyond traditional keyword parameters. Announced on May 6, 2025, the feature promises 14% conversion improvements through machine learning algorithms that analyze existing keywords, creative assets, and landing pages to identify relevant search opportunities.

Search Term Matching: The core functionality that expands keyword reach using broad match and keywordless technology to discover previously inaccessible search queries. This mechanism operates independently of traditional keyword targeting, instead leveraging artificial intelligence to identify relevant user searches based on campaign context and historical performance data. The system prioritizes matches similarly to existing Search and Performance Max campaigns while extending reach into long-tail and question-based queries.

Keywordless Technology: An advanced targeting method that operates without traditional keyword triggers, instead relying on artificial intelligence to match advertisements with relevant search queries. Testing data indicates that the majority of AI Max impressions utilize keywordless matching rather than conventional keyword associations. This represents a fundamental shift from traditional search advertising, where specific keywords directly influenced ad delivery and performance measurement capabilities.

Performance Max Campaigns: Google's automated campaign type that leverages artificial intelligence to optimize ad placement across Search, Display, YouTube, Gmail, Discover, and Maps properties simultaneously. These campaigns serve as the foundation for many AI Max comparisons due to their similar automation-first approach and historical development challenges. Performance Max campaigns became central to Google's advertising strategy and provide context for understanding AI Max's position within Google's broader automation ecosystem.

Conversion Rate: The percentage of users who complete desired actions such as purchases, form submissions, or newsletter subscriptions after clicking advertisements. Industry testing reveals that 99% of AI Max impressions generate zero conversions despite extensive search term matching activity. This metric represents the primary concern among advertising professionals evaluating AI Max effectiveness compared to traditional Search campaign performance standards.

Long-tail Search Terms: Extended search queries typically exceeding 25 characters that express specific user intent through detailed or question-based language. AI Max testing data shows that 31% of matched search terms fall into this category, often representing highly specific but low-converting traffic. These queries frequently involve conversational language patterns that reflect how users interact with artificial intelligence-powered search experiences.

Text Customization: Previously known as "automatically created assets," this feature generates headlines and descriptions based on landing pages, existing advertisements, and keyword data. The system creates adaptive creative content that aligns with emerging search intent patterns while maintaining brand consistency. Google reports improved ability to generate assets featuring clear calls-to-action and unique selling points through enhanced artificial intelligence capabilities.

Final URL Expansion: Technology that automatically directs users to optimized website pages rather than specified landing page destinations. This feature analyzes website content to identify the most relevant pages for specific search queries, potentially improving user experience and conversion rates. However, the automation requires careful configuration to prevent traffic direction to inappropriate website sections or restricted content areas.

Brand Controls: Precision targeting features that allow advertisers to specify exact brand associations or prevent advertisements from appearing alongside specific competitors. These controls operate at both campaign and ad group levels, addressing longstanding concerns about brand safety in automated advertising environments. The functionality provides advertisers with granular control over brand representation while maintaining artificial intelligence-driven optimization benefits.

Learning Period: The initial 1-2 week timeframe during which AI Max systems analyze campaign data and optimize performance parameters before achieving stable operation. Professional recommendations emphasize avoiding performance evaluations during this period, instead focusing on 4-6 week assessment windows after learning completion. This concept reflects the machine learning nature of Google's advertising systems, where algorithms require sufficient data collection before delivering consistent results.