Google transitions from dynamic Search Ads to AI Max

As part of its global strategy to automate advertising tools, Google has officially announced the transition of AI Max out of beta. This solution is designed to replace traditional Dynamic Search Ads (DSA), offering advertisers a superior level of targeting precision and scalability.

According to Google’s internal data, switching to AI Max delivers an average 7% increase in conversions or conversion value while maintaining stable performance metrics (CPA/ROAS). For medium and large-scale businesses, this update represents a paradigm shift: moving from manual semantic management to strategic AI signal orchestration.

Technological advantages: AI Max vs. DSA

Traditional DSA campaigns relied primarily on scanning website content. AI Max significantly expands this model by integrating:

• Real-time Intent Signals: Analyzing millions of search contexts to identify queries that fall outside standard semantic reach.
• Advanced Control Mechanisms: The introduction of specific brand filters and text guidelines allows major brands to maintain strict control over their Tone of Voice and Brand Safety.
• Asset Synergy: The ability to combine Automatically Created Assets (ACA) with advertiser-provided inputs to generate highly relevant creatives.

Migration timeline and process

The update process will take place in two distinct phases:

1. Voluntary Adoption Phase (Ongoing): Advertisers currently have access to tools for manually porting historical data and settings. This is a critical stage for preserving the performance of existing campaigns.
2. Automatic Migration (September 2026): All active campaigns utilizing DSA, automatically created assets, or campaign-level broad match settings will be automatically upgraded to the AI Max architecture. The ability to create new DSA campaigns will be discontinued.

Strategic recommendations for marketers and CRO specialists

To ensure a seamless transition and maximize performance, the following steps are recommended:

Synchronization of SEO and paid search

Since AI Max analyzes site content even more deeply, the quality of technical optimization and landing page relevance are now critical success factors. It is recommended to audit content hierarchy and utilize the data-nosnippet attribute to exclude technical site blocks from algorithmic analysis, preventing the generation of irrelevant headlines.

Executing pilot experiments

Before fully migrating budgets, advertisers should utilize the “One-click Experiments” feature. This allows for a split-test (A/B test) between the current DSA and the new AI Max model without risking core KPIs. Particular attention should be paid to monitoring potential traffic cannibalization between AI Max and existing Performance Max campaigns.

Strengthening brand safety protocols

To prevent non-target impressions, large-scale players should update account-level negative keyword lists and configure brand exclusions. This ensures that automation operates strictly within the defined brand positioning.

Leveraging enhanced analytics

AI Max provides more granular reporting on assets and search terms (Insight Reports). These data points should be used to adjust broader marketing strategies, as they reveal real-time shifts in consumer behavior and identify new growth opportunities previously unavailable for analysis.

The transition to AI Max is not merely a technical update, but a move toward intelligent scaling. Early adoption will provide businesses with a competitive edge, utilizing Google’s most advanced algorithms to capture high-intent audiences.

This article is available in Ukrainian.