Why your brand campaign might not be ready for AI Max

Recently, broad matching has been positioned as the future of paid search. Today, that role belongs to AI Max.

Over the past few months, I’ve heard repeated recommendations to enable AI Max in brand campaigns, even if those campaigns are already performing as intended.

The problem is that many accounts still lack the basics AI Max needs to function properly. Conversion tracking is unreliable, offline marketing for conversions is non-existent, and regular campaigns are often tied to budget or structure.

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

But using AI Max in a product means introducing more automation to your traffic source that is more predictable and efficient.

The promise and limitations of AI Max

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

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

Google has positioned AI Max as the next step in search automation, with DSA, automatically generated assets, and extensive match settings scheduled to switch to AI Max in September.

The platform includes controls such as branding, URL exclusion, text guidelines, and localization. For accounts with strong conversion tracking, sufficient search volume, and reliable performance signals, AI Max can uncover exponential growth opportunities.

Most accounts haven’t reached that stage yet.

Why the merits of AI are not a reason to rush to AI Max

Much of the recent interest in AI Max stems from Google’s push for an AI-powered search experience.

AI overview has now reached 2.5 billion users, according to Google. Ads appear in 25.6% of AI overview results, Semrush data shows.

As Google continues to expand its AI-driven search experience, marketers are understandably focused on maintaining visibility in all of these areas.

That concern is reasonable. The problem is that AI Max is often presented as a solution before marketers have addressed the issues of measurement, conversion, and account structure that determine whether automation can be successful.

Google Ads representatives often equip AI Max for product campaigns as required to qualify for AI Mode and AI Overview for product search. But this is not true.

Ginny Marvin, Google Ads consultant, confirmed that three campaign types are eligible for use in the AI ​​Overview: broad match Smart Bidding, Performance Max (PMax), and AI Max Search.

However, similar keywords are not eligible for use in AI Overview at all, even if similar 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 suitability. So if you’re using PMax product campaigns, you’re already covered. Adding AI Max won’t unlock anything new, as it will only add another layer of automation to an already decent setup.

So, when reps pitch AI Max to a product as an answer to the AI ​​niche, marketers should stop and ask why this feature takes precedence over improving the account base.

Test data does not support Google’s AI Max claims

While AI Max is in beta, Google said that advertisers who implement this feature will see 14% more conversions, and those using keywords that are exact matches to keywords will see a 27% increase in conversions.

Google also revealed that advertisers who enable the full AI Max feature see 7% more conversions on average. Independent tests have produced very mixed results.

The evidence for AI Max remains mixed

Across 600 accounts, Smart 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 on those accounts, indicating that advertisers are keeping budgets low.

After conducting four months of testing, Xavier Mantica found that AI Max has very expensive changes. While AI Max costs $100.37 per conversion, phrase matching costs $43.97 per conversion, and direct matching costs $52.69 per conversion. And Ezra Sackett tested 30,000 search terms with AI Max, but found that 99% of the ideas that came up brought zero conversions.

After analyzing 23 tests from 16 advertisers, Andy Goodwin noted improved Quality Score and ROAS when advertisers used the full-featured AI Max suite. But he tested mature advertisers and used text customization for only 50% of testing and URL optimization for 44%. This suggests that advertisers have been cautious about enabling all AI Max features.

However, none of this data is product specific. AI Max may deliver value in the right context, but a similar security product campaign that is already performing well is not the right place to test a new automation product that is highly dependent on signal quality. This is especially true for accounts that have not resolved the underlying data issues that feed them.

AI Max signals are weak in the product

AI Max doesn’t always find new search terms, according to Adalysis. In some cases, it just takes credit for direct questions and phrase campaigns that were already winning.

Because AI Max treats keywords as signals instead of targeting parameters, impressions that were supposed to include your exact match keyword may end up being attributed to AI Max instead.

This reporting issue can be important for brand campaigns. Product traffic is already high converting traffic for many accounts.

Turn on AI Max, and suddenly you see the height. But it’s hard to tell if it’s an increase or if the previous brand’s performance comes from a different bucket of automation.

Brand controls do not work consistently

Google’s pitch relies heavily on product controls. AI Max offers installed, uninstalled, and monitoring tools that are said to keep the game genre firmly in focus. In fact, these controls don’t always work well.

Adalysis notes that competitor terms sometimes creep in and brand terms sometimes match non-brand queries. DAC reports overlap between brand and non-brand names and unintended language pairings. And LBBOnline gets compliance running at around 50% for some campaigns.

Brand controls can evolve over time. But the available evidence does not support treating AI Max as a low-risk switch for tightly controlled security type campaigns.

What to consider before testing AI Max in a product

Before extending automation to a defensive brand campaign, ask these questions.

1. Are conversion signals reliable?

Have you separated major and minor changes? Does offline import work properly? Is lead quality returning to the platform, or is Google still improving equally across all forms filled?

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

2. Have you already tested the growth of generics?

In most of the accounts I audit, budget, poor landing page alignment, poor design, and general outdated query management campaigns. This is where you typically find incremental growth, not within an already strong brand campaign.

3. Does the account automatically provide enough useful learning data?

AI Max is not magic. It shows the quality of the signs under it.

If the majority of the account’s logical conversion volume comes from the brand, turning on AI Max for a brand campaign may reinforce existing reliance on product traffic rather than helping the account grow beyond it.

4. Is the brand + modifier search already set up correctly?

“Product + reviews,” “Product + price,” “Brand + near me,” and product objective variations usually deserve your campaign strategy perfectly. AI Max should not replace good account creation.

5. Do you have an important reason to expand the brand campaign?

If so, check carefully using the tests. That’s a business decision, not a check-box recommendation from a lawyer who hasn’t looked deep enough into the account to understand where the opportunities really are.

AI Max only works with self-supporting symbols

AI Max may grow into something really useful over time. Remember, PMax has gone through the same evolution and is in a much stronger place now than before.

But automation only works with the signals that feed it. Currently, the problem is that the foundations underlying automation are still not strong enough. Better conversion frameworks, measurement, account structure, and feedback loops make automation smarter.

If the brand remains the most effective campaign in the account, the big question is why the rest of the account hasn’t caught on.

Above all, don’t confuse Google’s default values ​​with your account’s values.