The way search advertising works is changing quickly, and the shift from Dynamic Search Ads to AI Max is one of the clearest signals yet of where platforms are heading.

 If you have relied on DSA as a scalable, catch-all solution, this transition is not just a product update.

It represents a broader move toward fully AI-driven campaign management.

What is AI Max?

AI Max is a new feature within Google Ads designed to enhance search campaigns using automation across targeting, creative, and landing pages.

Instead of relying purely on keywords or website scraping, it uses machine learning to interpret user intent in real time.

At its core, AI Max expands how campaigns match to search queries, generates and optimises ad copy dynamically, and can even adjust landing page destinations through automated URL selection.

It combines advertiser inputs like existing ads and website content with broader intent signals to reach users who might never have been captured through traditional keyword strategies.

What’s wrong with Dynamic Search Ads?

Dynamic Search Ads have been a useful tool for years. They allowed advertisers to fill gaps in keyword coverage by automatically generating headlines and matching queries based on website content.

The issue is not that DSA is broken, but that it is limited.

DSA relies heavily on landing page content as its primary signal. As search behaviour becomes more complex and less predictable, that approach struggles to keep up.

Users are searching in more nuanced ways, often with intent that cannot be mapped cleanly to a single page or keyword.

AI Max moves beyond this by incorporating real-time signals, broader query interpretation, and more advanced automation.

In simple terms, DSA looks at what your website says, while AI Max tries to understand what the user actually wants in that moment.

What does this mean for Performance Max?

Performance Max already represents a shift toward full automation across multiple channels, and AI Max brings similar principles into Search.

The distinction between campaign types is starting to blur.

Search is becoming less about tightly controlled keyword structures and more about feeding high-quality data into AI systems. Performance Max and AI Max are part of the same direction of travel, where automation handles execution and marketers focus more on inputs, strategy, and measurement.

This does not mean Performance Max becomes redundant.

Instead, it suggests a future where both campaign types operate as complementary AI-driven systems rather than fundamentally different approaches.

What does this mean for marketers?

For marketers, this is both an opportunity and a challenge.

There is less emphasis on manual optimisation such as keyword sculpting and more emphasis on guiding AI effectively.

Control is shifting. You are no longer deciding exactly which search term triggers which ad. Instead, you are setting parameters, feeding data, and shaping outcomes through signals like creative, audience insights, and conversion tracking.

This means the skill set evolves. Understanding how to structure data, interpret automation, and test incrementally becomes more important than granular manual control.

AI Max also introduces more detailed reporting on how assets perform against metrics like conversions and spend, rather than just impressions.

It adds visibility into headlines and URLs within search term reports, along with indicators showing why ads were matched. While this does not fully solve the black box problem, it is a step toward giving advertisers more insight into automated decision making.

For marketers who have been frustrated with limited visibility in other AI-driven campaign types, this is a meaningful development. 

A big change to experimentation 

An important area to highlight is how existing features are being consolidated into AI Max.

Tools like automatically created assets, broad match settings, and brand controls will no longer be standalone features. They are being absorbed into a single, unified system.

This reflects a bigger shift in platform design.

Instead of giving advertisers multiple levers to pull independently, Google is grouping them into one AI-led framework.

For marketers, this reduces fragmentation but also removes the ability to isolate and test individual elements in the same way as before.

It changes how experimentation works and pushes you toward testing full systems rather than individual tactics. 

What does this mean for brands?

For brands, consistency and clarity become critical. AI Max generates and adapts messaging dynamically, which means your underlying assets need to be strong and aligned.

Brand safety controls have improved, allowing advertisers to define where they do and do not want to appear, but there is still a level of trust required. If your messaging, landing pages, or offers are unclear, AI will amplify that inconsistency.

On the positive side, brands that provide strong inputs can scale faster and reach new audiences more efficiently than before.

What does this mean for keywords? 

There is a misconception that keywords are disappearing entirely.

According to Google, keywords are still a core signal that feeds the algorithm.

The difference is that they are no longer the primary control mechanism. Instead of acting as strict targeting rules, they function more like guidance for the AI.

This is a subtle but important shift.

Keyword strategy becomes less about coverage and sculpting, and more about providing high-quality intent signals that the system can learn from and expand upon. 

What are the current issues with AI Max?

Despite the promise, AI Max is not without its challenges.

Transparency is still a concern.

While reporting has improved, it is not always easy to understand exactly why certain decisions are being made.

There are also technical considerations. Automated landing page selection can conflict with tracking setups, particularly if tracking templates are not configured correctly. This can lead to broken URLs or poor user experiences if not carefully managed.

Control is another common concern. Even with new settings for brand and location targeting, some advertisers feel they are giving up too much precision compared to traditional keyword strategies.

Finally, performance claims should be treated cautiously.

While early data suggests improvements in conversions at similar efficiency, results will vary significantly depending on how well campaigns are set up.

Should we be using it right now? Can we?

Yes, AI Max is already available and being rolled out more widely.

Advertisers can adopt it now rather than waiting for automatic migration.

Using it early allows you to test, learn, and refine your setup before it becomes the default. Waiting until forced migration risks losing control during a transition period when performance stability matters most.

Can I carry on using Dynamic Search Ads instead?

Short answer – no.

This is not a soft transition.

From September, advertisers will no longer be able to create new Dynamic Search Ads campaigns, and existing campaigns using DSA, automatically created assets, or campaign-level broad match will be automatically upgraded.

That means even if you choose to ignore AI Max for now, you will eventually be moved onto it.

The important nuance here is that campaigns will be migrated with settings designed to mirror existing setups, which helps protect performance in the short term. However, relying on this default setup means you are effectively letting Google make strategic decisions on your behalf, rather than shaping the structure yourself.

This makes a strong case for early adoption and controlled testing rather than waiting for the switch to happen to you. 

Should we move everything to AI Max?

It would be risky to rely entirely on any single campaign type.

While AI Max is clearly a major focus, a balanced approach is still important.

Different campaign types serve different purposes. Standard search campaigns, Performance Max, and even other channels all contribute unique value. AI Max should be part of a broader strategy rather than replacing everything outright.

Testing is key. Running AI Max alongside existing approaches allows you to compare performance and understand where it fits best.

Are Microsoft following suit?

Yes, Microsoft is moving in a similar direction.

Their version of AI Max within Microsoft Advertising expands query matching and personalises ad delivery across AI-driven environments like Bing and Copilot.

This reinforces that the shift is not limited to one platform. The entire search ecosystem is evolving toward AI-led discovery, where both users and even AI agents play a role in decision making.

In conclusion…

The move from Dynamic Search Ads to AI Max is not just a feature upgrade and it is not happening in isolation.

It reflects a world where search queries are longer, more conversational, and often handled within AI-driven environments, and signals a broader transformation in how search advertising works.

The platforms are preparing for a future where users may not even interact with traditional search results in the same way.

AI and Automation is no longer an add-on. It is becoming the foundation.

Marketers who adapt early, focus on strong inputs, and embrace testing will be better positioned as this shift accelerates.

The key is not to resist the change, but to understand where human strategy still adds value in an increasingly automated environment.