AI Max by Google: Promise versus Reality

With AI Max, Google takes another step toward fully automated search advertising. During this year’s Friends of Search event, significant attention was paid to AI Max in Google’s session. Less reliance on keywords and greater trust in AI: that is the core of the proposition. But how does this promise compare to reality?

What does Google promise with AI Max?

According to Google, AI Max should deliver several fundamental improvements within search:

• Unlocking new search demand through broader, AI-driven matching.

• More conversions through smarter use of data and website content.

• More efficient budget allocation through automatic optimization.

• Better alignment with search intent via dynamic landing pages.

The implicit promise is clear: more reach and better performance, without additional manual work.

What do we see in practice?

We activated AI Max for multiple advertisers, including an automotive client, and compared the results with non–AI Max search match types.

Limited new reach

What stands out immediately is that a large share of the traffic generated via AI Max was previously already captured by non–AI Max keywords. Rather than unlocking new demand, AI Max so far mainly seems to redistribute existing demand.

The additional search queries generated by AI Max are primarily long-tail and relatively small in scale; specifically, this accounted for less than 7 percent of total AI Max volume.

Inconsistent performance

AI Max performance does not show a uniform pattern and differs by segment. We tested this with an automotive client in generic campaigns.

• For SUVs: CPA decreased by 16 percent, CTR increased by 17 percent, and CPC decreased by 18 percent.

• For small cars: CPA increased by 6 percent, CTR decreased by 7 percent, and CPC increased by 12 percent.

In many cases, non–AI Max search match types remain responsible for the majority of conversions. In our test, this was more than 70 percent.

What does this mean?

Taken together, AI Max currently functions primarily as an additional optimization layer on top of existing search campaigns, rather than as a clear driver of incremental growth.

Where does the real value lie?

A positive aspect is that AI Max appears to be better at matching search intent with the right landing page and ad copy. This can lead to improved performance within the volume that is already being realized. It also provides interesting insights, such as which AI-generated ad copy combinations perform better than existing texts and whether other web pages convert more effectively.

How should AI Max be approached?

The introduction of AI Max requires a realistic and critical approach:

• See it as an addition, not a replacement
  The current keyword structure remains essential for now. AI Max works best as an additional layer.

• Stay critical on incrementality
  Does it add value that would not otherwise have existed? We often see branded searches appearing within generic AI Max campaigns, which can distort the view of true performance.

• Apply it selectively
  Impact differs by situation. In general, we see more added value in generic campaigns due to the high volume of variations compared to brand campaigns.

• Exclusions are crucial
  Closely monitor search term reports. Standard exclusion lists do not always integrate seamlessly with AI Max, so it is important to review this carefully during the first weeks to filter out irrelevant traffic.

Conclusion

With AI Max, Google once again reinforces the move toward further automation. The direction is clear, but practical results show that the impact does not yet consistently match the promise. For marketers, this means one thing: continue testing, remain critical, and do not let automation fully dictate strategy. AI is improving rapidly, but it is not yet a replacement for a well-considered search strategy.