A recent test run by the Adalysis team reveals that Google’s new AI Max setting is reshaping how search terms are matched and reported — creating blind spots for advertisers who rely on precise keyword control.
When AI Max isn’t the right fit. AI Max isn’t inherently bad, but advertisers should think twice if:
- Broad match historically underperforms in your account.
- Your top exact/phrase match keywords are already constrained by budget.
- You prefer not to use text customization or Final URL expansion — both built-in components of AI Max.
If you only need broad match, you can add those keywords manually and keep full control.
How AI Max interacts with your keywords. The Adalysis test shows that if your campaign doesn’t include a broad match version of a keyword, AI Max effectively acts as if it does — and Google assigns impressions, clicks, and cost to your existing keywords.
This blurs match-type reporting and can give AI Max credit for traffic your exact and phrase match terms were already earning.
The recommended fix: add broad match versions of your core keywords to restore clean reporting.
The search-term reporting problem. When search terms were reviewed under AI Max, consistent issues were found: brand terms matching to non-brand queries, non-brand terms matching to competitors, and occasionally brand queries matching to competitor terms.
Brand filters help but misspellings and variants still leak through, so strong negative keyword lists remain essential.
AI Max isn’t always finding new searches. Often, AI Max isn’t discovering new queries — it’s simply taking credit for your existing ones. It can even override Google’s normal matching hierarchy, assigning impressions to AI Max instead of identical keywords in more relevant ad groups.
That’s partly why its performance metrics look artificially strong.
The mystery bucket. The team also found AI Max search terms that don’t map to any keyword in the account — unrelated to landing page content or past searches. This may tie to Google’s keywordless technology, but Google hasn’t confirmed.
To get an accurate view of AI Max’s impact, Adalysis recommends de-duplicating search terms across match types to separate true incremental performance from reassigned results.
Google’s priority order — in theory. Google says exact match should win when the search term is identical. In practice, the Adalysis test showed AI Max sometimes overriding this logic, forcing advertisers to add even misspellings and close variants as exact match to protect high-value queries.
Why we care. This test shows that AI Max can quietly override match types, reassign performance, and blur reporting — making it hard to understand what’s actually driving results. If you can’t trust which keywords triggered which queries, you can’t optimize budgets, protect brand traffic, or measure true incremental performance.
The bottom line. Adalysis’ testing confirms that while AI Max can help scale campaigns, its reporting structure can inflate perceived performance by reallocating impressions from exact and phrase match.
If you’re using or testing AI Max, add broad match versions of all keywords, separate brand/non-brand/competitor traffic with strong negatives, keep adding your top queries as exact match, and monitor for duplicated or misrouted search terms.
Even in the AI era, search-term management remains critical to ensuring your budget flows to the queries that actually perform.
Dig Deeper. Interesting reads about AI Max:
- AI Max for Search: Everything you need to know
- How to tell if Google’s AI Max for search is actually working
- Testing AI Max in Google Ads: When to try it and when to wait
- AI Max in action: What early case studies and a new analysis script …
- Google doubles down on AI Max pitch to wary advertisers
- Google Ads begins rolling out AI Max for Search