Since September 1, 2026, Google has been automatically upgrading eligible Search campaigns to AI Max — a change this project’s earlier migration guide covered in detail. For most advertisers, that upgrade already happened without a choice being made. The question now isn’t whether to adopt AI Max — many accounts already have it — but whether to expand it, restrict it, or actively fight its defaults before locking festive-season budgets. Several independent researchers have now tested that question with real campaign data, rather than relying on Google’s own marketing claims. This piece walks through what they found.
Search Engine Journal’s coverage of Smarter Ecommerce’s (SMEC) research notes that Google has told advertisers: “Advertisers who activate AI Max typically see 14% more conversions or conversion value at a similar CPA or ROAS” — a figure that excludes retail accounts specifically. That is Google’s own official performance claim, and it’s a reasonable starting benchmark against which to compare independent data.
Smarter Ecommerce (SMEC), published March 5, 2026 — 250+ campaigns, roughly 1 million AI Max impressions. Mike Ryan’s analysis found a median revenue increase of +13% — close to Google’s own 14% claim — but alongside a median CPA increase of +16%. ROAS results varied enormously, from +42% to −35% depending on the account, with only 22% of campaigns holding their original ROAS targets. Ryan’s own conclusion, as reported: “Turning on AI Max is essentially a coin toss: you may see a lift, but efficiency likely won’t follow.” The study also found broad-match query cannibalization occurring in up to 63% of accounts examined, and that nearly half of advertisers were running AI Max alongside Dynamic Search Ads and Performance Max simultaneously — creating overlap and conversion-tracking fragmentation. At the time of that study, only about 16% of advertisers were actively testing AI Max, and few had gone all-in on its full feature set.
Search Engine Land’s 23-test analysis, published March 12, 2026 — 16 advertisers, 9 months. This broader study found that campaigns using all three AI Max features together (search term matching, text customization, and URL optimization) showed a 40% higher rate of test success than using search term matching alone. Text customization specifically lifted the account’s weighted-average Quality Score from 6.8 to 7.3. But the same study found only 46% of queries pulled into AI Max campaigns were genuinely new to the account — meaning more than half of AI Max’s apparent reach was queries the account was likely already capturing another way — and the net incremental conversion-value lift, account-wide, worked out to roughly 3%, once that overlap was accounted for. Adoption of the full feature set was also partial: only 50% of test cases enabled text customization, and 44% activated URL optimization.
A separate independent analysis, reported by PPC Land on November 6, 2025 — a second SMEC dataset (250+ retail campaigns, 600+ accounts) plus a four-month single-advertiser test. This SMEC retail-specific dataset found AI Max delivering conversions at roughly 35% lower ROAS than traditional match types, with higher cost per conversion and lower average order values — though AI Max represented only about 0.57% of total account-level spend across the accounts examined. Separately, advertiser Xavier Mantica’s own four-month test found AI Max costing $100.37 per conversion, compared with $43.97 for phrase match and $52.69 for exact match — AI Max underperforming every match type he tested, including close variants. His own summary, as reported: “I’m done with AI Max. After 4 months of testing, the data is brutal.”
To be fair to the platform side of this: Google’s Ads Liaison, Ginny Marvin, clarified in June 2026 (via Search Engine Land) that AI Max is not mandatory for appearing in AI Overviews or AI Mode results — broad-match campaigns remain eligible without it. She also pointed out a real measurement limitation that cuts both ways: ads shown inside AI Overviews and AI Mode currently have no separate, placement-level performance reporting, meaning some of the disagreement between Google’s claims and independent testing may reflect genuine reporting-visibility gaps, not just differing methodology. Marvin’s guidance to advertisers focused less on AI Max itself and more on three underlying priorities: first-party data quality (via tools like Enhanced Conversions and Data Manager), a new long-window measurement option called Qualified Future Conversions (tracking conversions up to 180 days later — notably relevant for B2B and lead-generation businesses), and upcoming “AI Brief” controls for giving AI Max explicit do/don’t instructions.
Three things are true at once, and none of them cancel the others out:
This is not a case of one flawed study versus Google’s marketing. Multiple independent analyses, across hundreds of campaigns and different account types, arrive at a similar shape of result: some revenue upside, real and repeated efficiency cost, and wide account-to-account variance.
Google has continued investing in the feature — in August 2026 it added multi-campaign A/B testing (rolling out from September 2026), brand and location controls for experiments, and an expanded Performance Planner for forecasting AI Max’s budget and bidding impact. These are genuinely useful tools for the exact evaluation this article recommends: before increasing AI Max’s share of festive-season budget, run a controlled A/B test using Google’s own new experiment tools, watch CPA and ROAS separately from conversion volume, and check search-term reports for cannibalization of queries the account was already winning through other match types.
Google’s AI Max may drive higher revenue, but independent data shows CPAs can quietly spike by double digits if left unmonitored. Before locking in your Q4 spend, let our team audit your search accounts, implement strict brand/location controls, and launch controlled A/B experiments to protect your bottom line.
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