Treating AI Max as Expansion Rather Than Optimization

Moving from Dynamic Search Ads (DSA) to AI Max changes Google Ads strategy from precise search intent to broad information gathering. While Google presents this as a way to grow, it often breaks the link between a user search and the correct landing page. For those running lead generation or e-commerce campaigns, this creates an operational burden. The best approach is to treat AI Max as an expansion tool rather than an optimization tool, testing it separately instead of using it to replace high-intent search structures.

The Hidden Cost of Replacing Granular Control

Replacing DSA with AI Max changes how the system handles intent. Joey Bidner points out that AI Max often fails to connect specific search terms to the right product pages, instead sending users to homepages or irrelevant collections. This happens because the algorithm prioritizes broad engagement over the specific product matching that actually leads to sales.

"I was getting good quality search terms, but they just weren't matching to granular or appropriate pages. I was getting a product level search term going to a home page, going to a generic collection page."

-- Joey Bidner

Features like brand and URL inclusions are essentially patches for this problem. By manually setting boundaries, such as using URL strings to keep the AI focused on specific categories, advertisers can regain some control. However, this requires constant management. The system does not fix the issue on its own; the operator must build guardrails to stop the algorithm from chasing irrelevant traffic.

Why AI Mode Often Misses the Mark for Advertisers

Chris Schaeffer notes a gap between Google's AI-first approach and the needs of small and medium businesses. Google's data shows that AI-mode searches often focus on informational intent, such as identifying or explaining topics, rather than the transactional intent needed for services like roof repair or photography classes.

"I couldn't be less interested in searches that sound like this. Absolutely not. ... I'm trying to sell photography classes. I'm trying to sell certain widgets I'm trying to get quotes for new roof repair."

-- Chris Schaeffer

The system is currently built for information retrieval, not lead conversion. Because one in six AI-mode searches involve images or voice, advertisers lose the ability to target with keyword precision. This forces advertisers to cast a wide net, which is the opposite of the optimization most businesses need. AI Mode is best used as an expansion tool for accounts that have already exhausted their high-intent search traffic, not as a replacement for standard search campaigns.

The Illusion of Experiment Results

A major risk with these new tools is the lack of transparency in testing. Schaeffer and Bidner warn against using the Test AI Max button in the Google Ads interface, as it often lacks a proper control group. Without a split-test structure, advertisers might mistake broad-match brand traffic for success driven by AI.

The advantage goes to those who avoid one-click testing. By manually building A/B tests at the account level with a true control group, advertisers can see if AI Max is actually adding value or just taking credit for traffic that would have converted through standard search anyway.

Key Action Items

• Audit your current campaign structure: If you are moving from DSA to AI Max, do not assume it will be a smooth transition. Use brand and URL inclusions right away to stop irrelevant traffic from reaching your homepage.
• Adopt a reactive governance model: Because AI Max changes ad copy on its own, use term exclusions to block irrelevant messaging or locations as you see them in your search term reports.
• Reject the Test AI Max button: Over the next few months, ignore automated experiment prompts. Build manual A/B tests at the account level to ensure you have a control group for reliable data.
• Re-evaluate your goal alignment: If your business relies on high-intent, transactional leads, treat AI Max as an expansion-only experiment. It is not an optimization tool.
• Monitor the search-to-landing-page correlation: Use the term and ad combinations report to check that search terms are landing on the right product pages. If the match is poor, tighten your URL inclusion rules.
• Wait for feed-based integration: Watch for future updates regarding shopping feeds. If Google eventually lets AI Max use product feeds instead of URL scraping, re-test the tool in 12 to 18 months.