Google is moving automation in Google Ads from optional feature to mandatory infrastructure for Search campaigns. The company announced a migration schedule: automatic conversion of legacy Search campaign features to AI Max will begin in September, with Dynamic Search Ads set to follow next year.
For advertisers this means a shift in traffic management approach. Controlling campaigns purely through keywords, exact match and manual segmentation will become harder. Data quality, goal accuracy, feed structure and the ability to quickly assess incremental results from automated decisions will matter more.
What changes in Search campaigns
AI Max is a set of Google's automated capabilities for expanding reach and optimizing search advertising. The system uses signals about user intent, landing page content, ad assets and conversion data to match queries, audiences, ad copy variants and destination pages.
The key change is not just a new interface feature. Google is gradually moving advertisers from separate legacy mechanics to a more unified model where the algorithm gets more freedom to choose the combination of query, ad and landing page.
Automatic migration from September will affect legacy Search campaign features. Individual settings and scenarios may be transferred in stages, so exact behavior will depend on campaign type, region, bidding strategy and features in use. DSAs retain separate status for now, but their transition to the new model is expected next year.
For iGaming and affiliate teams this is especially important. The vertical often uses different GEOs, languages, payment scenarios and monetization models: CPA, hybrid or revshare. An error in conversion settings or excessive reach expansion can quickly degrade traffic quality, even when CTR and registration numbers grow.
Why migration affects traffic economics
With manual management teams typically define a set of commercial queries, negative keywords, geography, scheduling and budget allocation logic in advance. AI Max can find additional demand variants and independently connect them with available campaign assets.
This creates two effects.
First, potential reach grows. Campaigns can get impressions on formulations not included in the semantic core. For new GEOs or narrow offers this helps find converting segments faster.
Second, predictability drops. Additional reach does not equal additional profit. The algorithm may bring users with weaker intent, and in regulated verticals advertisers risk encountering irrelevant context, policy restrictions or landing page-to-ad mismatch issues.
Evaluating migration by CTR alone will not work. You need the full metric chain: spend, clicks, registration, confirmed deposit, FTD, player revenue, CPA or actual ROI. For revshare it helps to separate early signals from delayed value: a registration today may generate revenue over weeks, and an algorithm trained only on registrations will start optimizing for cheap but weak leads.
What to check before automatic transition
1. Goals and conversion tracking
Before migration run a conversion tracking audit. Check which events are passed to Google Ads and which are marked as primary. For an iGaming funnel these might be visit, registration, account confirmation, first deposit and repeat deposit.
If registration alone is used as the main goal, AI Max will look for users inclined to register, not necessarily deposit. In a CPA model this directly affects approval quality and final ROI.
Separately verify:
- no duplicates when passing events via tag, API and server tracking;
- correct currency and conversion value;
- delay between event and its sending;
- transmission of lead status and cancelled conversions;
- separate analytics by GEO, device and source.
2. Campaign and budget structure
Do not combine regions with different economics in one campaign. Ukraine, Kazakhstan, Uzbekistan and other CIS markets may differ substantially in CPM, purchasing power, deposit conversion and LTV. With automation expanding the algorithm needs clear boundaries: separate budgets, goals and landing pages for segments with different commercial potential.
If one offer works on CPA and another on revshare, better analyze them separately. They have different acceptable CPA, payback horizons and sets of meaningful events.
3. Landing pages and ad assets
AI Max gets more freedom in choosing the ad-to-page combination. The site becomes part of algorithmic optimization, not just the final click destination.
Check that landing pages have:
- clear offer and bonus terms description;
- matching language, GEO and currency;
- no contradictions between ad and actual offer;
- fast mobile version loading;
- working registration, payment methods and tracking;
- necessary age and legal restrictions.
For testing it helps to create separate pages for different intents: branded query, promo, specific sport or casino product. This lets you understand which combinations actually improve conversion versus merely increasing cheap traffic volume.
How to measure AI Max effect
Transition cannot be evaluated by before-and-after comparison without accounting for seasonality, bid changes and other channel activity. Minimum observation period should include enough conversions for strategy learning, but not so long that inefficient traffic manages to spend substantial budget.
Fix baseline values for several weeks before migration:
- CTR and average cost per click;
- impression share on branded versus non-branded semantics;
- click-to-registration conversion;
- registration-to-deposit or approved-action conversion;
- CPA, ROAS and actual revenue;
- mobile and desktop traffic share;
- traffic quality by GEO and partner sources.
After transition analyze not just the campaign as a whole but search queries, intent categories, destination pages and conversion types. If Google shows limited detail, use your own analytics, postbacks and tracker data. In affiliate setups the tracker often gives a more honest picture of FTD, holds and cancellations.
A good test criterion for iGaming teams is not maximum registration count but growth in confirmed margin with controlled CPA. If campaigns run on revshare, additionally account for payback period and cohort quality.
Practical plan for teams
Preparation can be divided into several stages.
- Inventory. List Search campaigns, legacy features in use and associated offers.
- Data audit. Check goals, conversion values, deduplication and event passing from tracker.
- Baseline capture. Save spend, conversion and revenue metrics before migration starts.
- Asset cleanup. Update copy, images, extensions, landing pages and legal disclaimers.
- Economics separation. Separate GEOs, CPA and revshare models, and branded versus generic demand if needed for control.
- Post-transition monitoring. Track spend and technical failures daily, assess conversion quality over a longer horizon.
Antidetect, proxies and other technical infrastructure tools do not solve weak data problems. If tracking does not distinguish registration from deposit, the algorithm will optimize the wrong result regardless of the stack used.
Main takeaway
Automatic migration to AI Max does not eliminate the role of advertising specialists but changes it. Manual semantic building remains important for brand control, policy and traffic quality, but the main competitive advantage increasingly forms around data: correct events, clean analytics, strong landing pages and realistic offer economics.
By September prepare not just ad campaigns but the measurement system. And treat next year's DSA transition as a continuation of the same trend: Google is gradually consolidating search inventory and handing more decisions to algorithms. The more precisely a team defines valuable conversion and acceptable ROI, the safer it will be to scale reach without losing quality.
