Why your brand campaign may not be ready for AI Max

Not long ago, broad match was positioned as the future of paid search. Today, that role belongs to AI Max.

Over the last few months, I’ve heard repeated recommendations to enable AI Max on brand campaigns, even when those campaigns are already performing exactly as intended.

The problem is that many accounts still lack the foundations AI Max needs to work well. Conversion tracking is unreliable, offline conversion imports are missing, and generic campaigns remain constrained by budget or structure.

AI Max depends on strong conversion signals, sufficient volume, and enough variation for the system to learn effectively. In many accounts, brand campaigns provide most of that signal. 

But using AI Max on brand means introducing additional automation into your most predictable and efficient traffic source.

The promise and limitations of AI Max

AI Max expands search targeting beyond your existing keyword list by using keywords, landing pages, and site content as signals rather than strict targeting parameters.

Like dynamic search ads (DSA), AI Max can match to queries you didn’t explicitly target. But it goes further, reaching beyond the intent boundaries defined by your keyword set.

Google has positioned AI Max as the next step in Search automation, with DSA, automatically created assets, and campaign-level broad match settings scheduled to transition into AI Max in September.

The platform includes controls such as brand exclusions, URL exclusions, text guidelines, and location targeting. In accounts with strong conversion tracking, sufficient search volume, and reliable performance signals, AI Max may uncover incremental growth opportunities.

Many accounts haven’t reached that stage yet.

Why AI surface eligibility isn’t a reason to rush into AI Max

Much of the recent interest in AI Max stems from Google’s push toward AI-powered search experiences.

AI Overviews now reach 2.5 billion monthly users, according to Google. Ads appear in 25.6% of AI Overview results, Semrush data shows.

As Google continues expanding AI-driven search experiences, advertisers are understandably focused on maintaining visibility across those surfaces.

That concern is reasonable. The problem is that AI Max is often presented as the solution before advertisers address the measurement, conversion, and account structure issues that determine whether the automation can succeed.

Google Ads representatives typically pitch AI Max for brand campaigns by claiming it’s necessary for eligibility in AI Mode and AI Overviews on brand searches. But this isn’t accurate.

Ginny Marvin, Google Ads liaison, confirmed that three campaign types are eligible to serve in AI Overviews: broad match with Smart Bidding, Performance Max (PMax), and AI Max for Search.

However, exact match keywords aren’t eligible to serve in AI Overviews at all, even when identical broad match keywords exist in the same account.

So, the eligibility picture looks like this:

PMax and AI Max do broadly the same job in terms of AI surface eligibility. So if you run PMax brand campaigns, you’re already covered. Adding AI Max won’t unlock anything new, as it’ll only add another automation layer to a setup that’s already eligible.

So, when reps position AI Max on brand as the answer to AI surface eligibility, advertisers should stop and ask why this feature takes priority over fixing the account’s foundation.

Test data doesn’t support Google’s AI Max claims

When AI Max was in beta, Google stated that advertisers who activate the feature would see 14% more conversions, and those running exact and phrase match keywords would likely see a 27% increase in conversions.

Google also indicated that advertisers who enable the full AI Max feature suite see 7% more conversions on average. Independent testing has produced more mixed results.

The evidence for AI Max remains mixed

Across 600 accounts, Smarter Ecommerce found that AI Max delivered a 35% lower return on ad spend (ROAS) than traditional match types. AI Max accounted for just 0.57% of total ad spend in those accounts, indicating that advertisers kept the budget to a minimum.

After running a four-month test, Xavier Mantica found that AI Max had the most expensive conversions. While AI Max cost $100.37 per conversion, phrase match cost $43.97 per conversion, and exact match cost $52.69 per conversion. And Ezra Sackett tested 30,000 search terms with AI Max, only to find that 99% of impressions delivered zero conversions.

After a 23-test analysis of 16 advertisers, Andy Goodwin noted improved Quality Score and ROAS when advertisers used the AI Max full feature suite. But he tested mature advertisers and used text customization in only 50% of tests and URL optimization in just 44%. This suggests advertisers were cautious about enabling every AI Max feature.

However, none of this data is brand-specific. AI Max may deliver value in the right context, but an exact match defensive brand campaign that already performs well isn’t the ideal place to test a new automation product that depends heavily on signal quality. This is especially true for accounts that haven’t solved the underlying data problems feeding the automation.

AI Max attribution gets murky on brand

AI Max doesn’t always find genuinely new search terms, according to Adalysis. In some cases, it simply takes credit for the queries that exact and phrase campaigns were already winning.

Because AI Max treats keywords as signals rather than targeting parameters, impressions that would previously have been attributed to your exact match keyword can end up attributed to AI Max instead.

This reporting issue can be significant for brand campaigns. Brand traffic is already the highest converting traffic in most accounts.

Flip on AI Max, and suddenly you see an uplift. But it’s difficult to tell if it’s incremental or if preexisting branded performance simply appears in a different automation bucket.

Brand controls don’t work consistently

Google’s pitch leans heavily on brand controls. AI Max offers inclusions, exclusions, and guardrails that supposedly keep the match type tightly focused. In practice though, these controls don’t always work well.

Adalysis notes that competitor terms occasionally slip through and brand terms sometimes match to non-brand queries. DAC reports overlap between brand and non-brand terms as well as unintended language matching. And LBBOnline finds relevance hovering around 50% in some campaigns.

Brand controls could improve over time. But the available evidence doesn’t support treating AI Max as a low-risk switch for tightly controlled defensive brand campaigns.

What to consider before testing AI Max on brand

Before expanding automation into a defensive brand campaign, ask these questions.

1. Are the conversion signals trustworthy?

Have you separated macro and micro conversions? Do offline imports work correctly? Does lead quality feed back into the platform, or does Google still optimize equally toward every form fill?

If the signal quality underneath the account is poor, AI Max will amplify it instead of fixing it.

2. Have you already explored generic growth?

In many of the accounts I audit, budget, weak landing page alignment, poor structure, and outdated query management limit generic campaigns. This is where you usually find incremental growth, not inside an already dominant brand campaign.

3. Does the account give automation enough useful learning data?

AI Max isn’t magic. It reflects the quality of the signals underneath it.

If most of the account’s meaningful conversion volume comes from brand, then turning AI Max on in a brand campaign may reinforce existing dependency on branded traffic rather than helping the account grow beyond it.

4. Are brand + modifier searches already structured properly?

“Brand + reviews,” “Brand + pricing,” “Brand + near me,” and product intent variations often deserve their own campaign strategy entirely. AI Max shouldn’t become a substitute for good account architecture.

5. Do you have a strategic reason to expand the brand campaign?

If so, test carefully using experiments. That’s a business decision, not a checkbox recommendation from a rep who hasn’t looked deeply enough at the account to understand where the real opportunities actually are.

AI Max only works as well as the signals feeding it

AI Max may grow into something genuinely useful over time. Remember, PMax went through a similar evolution and is in a much stronger place now than it was early on.

But automation only works as well as the signals feeding it. Right now, the issue is that the foundations underneath the automation still aren’t strong enough. Better conversion frameworks, measurement, account structure, and feedback loops make automation smarter.

If brand remains the best-performing campaign in the account, the bigger question is why the rest of the account hasn’t caught up yet. 

Above all else, don’t confuse Google’s automation priorities with your account priorities.