Google is making AI Max easier for Italian advertisers to steer and preparing a reporting layer designed to expose one of the most opaque parts of automated Search advertising: the full path from the user’s query to the creative Google assembled and the landing page its AI selected.
In an official announcement published September 23, Google said the closed beta of AI Brief is expanding to Italian alongside Dutch, French, German, Japanese, Portuguese and Spanish. AI Brief lets advertisers guide AI Max in natural language by describing their business, the audience they want to reach and the messages they want the system to emphasize.
Google is also preparing a new AI Max reporting feature that will place the Search ad journey into one unified view. Advertisers will be able to see which search terms triggered an ad, which creative assets the user saw and exactly where that user landed on the advertiser’s website. Google has not yet announced general availability: it says additional details and timing will arrive later in 2026.
Together, the two changes attack opposite sides of the same automation problem. AI Brief gives advertisers more expressive input before Google’s AI makes decisions, while the new report is intended to reveal more of what happened after those decisions were made.
Italian advertisers can now brief Gemini in Italian
AI Brief is powered by Gemini and is designed to replace part of the rigid configuration language traditionally associated with paid search with natural-language guidance.
Instead of expressing every strategic preference through keywords, exclusions, asset fields and isolated campaign settings, advertisers can give AI Max richer context about what the business does, which audiences matter and how messages should be framed.
Google’s earlier AI Brief documentation breaks that steering into several practical categories. Messaging guidelines can tell the system what ads should or should not say. Matching guidelines can establish boundaries around the searches the advertiser wants to capture or avoid. Audience guidelines can describe the people the campaign is trying to reach and the benefits that should be emphasized for them.
The September expansion means Italian-language teams can now provide that context directly in Italian rather than translating strategic instructions into English simply to communicate with the campaign system.
This is still a closed beta, not a general rollout
The language expansion should not be mistaken for broad availability. Google explicitly describes AI Brief as a closed beta.
That means advertisers should not assume the feature is already present in every eligible Italian Google Ads account. Access remains controlled while Google tests the experience and gathers feedback.
The distinction matters because AI Max itself is already a major production product, while AI Brief is a newer steering interface layered on top of that automation. Google is expanding the languages in which selected advertisers can test the feature, not announcing universal access.
For agencies and in-house teams, the immediate change is therefore capability expansion for beta participants rather than a mandatory migration.
Prompting a campaign changes what “campaign setup” means
Paid search has historically required advertisers to translate commercial strategy into platform-specific objects: keywords, match types, ad groups, headlines, descriptions, audiences, URLs and bid settings.
AI Max already shifts some of those decisions toward automated matching and creative optimization. AI Brief pushes the interface further by allowing strategic intent itself to be expressed conversationally.
An advertiser can describe who should be reached and what the brand wants to communicate, then let Gemini help translate those instructions into campaign behavior. Google says AI Brief also provides previews of sample assets and searches so advertisers can give feedback and iterate before committing.
This does not eliminate structured controls, but it creates a new layer above them. The prompt increasingly becomes part of campaign configuration.
The new report is designed to expose the automation chain
More automation creates a reporting problem. If Google expands matching beyond manually selected keywords, assembles creative dynamically and uses AI to choose a destination page, a conventional performance table can tell the advertiser that a conversion happened without explaining the chain of decisions that produced it.
Google’s forthcoming report is designed to make that chain more legible. The company says advertisers will get a single unified view showing the search terms that triggered their ads, the creative assets the user saw and the exact location on the website where the user landed.
That sequence—query, creative, landing page—is especially important in AI Max because all three can be influenced by automation.
The report therefore promises something more useful than another aggregate AI performance metric. It could let advertisers inspect how Google translated an individual expression of intent into a particular message and destination.
Google has not yet published the full reporting specification
The announcement is a preview, not complete documentation. Google says it will share additional details and availability later this year.
Important questions therefore remain unanswered. Google has not yet described the exact reporting granularity, retention period, export options, privacy thresholds or whether every AI Max interaction will expose the same level of detail.
It is also too early to know how the interface will handle combinations of dynamically generated and advertiser-provided assets, or how easily teams will be able to aggregate query-to-landing-page paths at scale.
Those details will determine whether the new report becomes primarily a debugging tool or a serious optimization dataset.
The landing-page connection is particularly important for AI Max
AI Max can use final URL expansion to select a page it considers more relevant to a user’s search than the landing page an advertiser might have manually chosen for a narrower keyword structure.
That flexibility becomes increasingly useful as searches grow more conversational and specific. A large website can contain hundreds or thousands of possible destinations, and the most appropriate page can change with subtle differences in intent.
But automated destination selection also creates risk. A system can send high-value traffic to an unexpected page, expose outdated messaging or choose a technically relevant destination that performs poorly commercially.
A report connecting the triggering query directly to the final page should make those decisions much easier to audit.
Longer conversational queries make the path harder to predict manually
The reporting announcement arrives as Search behavior itself becomes more complex. NetContentSEO recently covered data showing that longer search terms are taking a larger share of impressions and conversions in one Google Ads dataset.
Google’s own product strategy points in the same direction. AI Max is designed to find relevant opportunities beyond literal keyword matching and respond to richer expressions of user intent.
As queries become longer, the number of possible query-to-ad-to-page combinations expands dramatically. Manual mapping becomes less realistic, which is precisely why Google is automating more of the chain.
The new report is effectively an observability layer for that combinatorial complexity.
AI Brief and journey reporting form a control loop
The most interesting way to read the announcement is not as two unrelated features. AI Brief and journey reporting can form a feedback loop.
The advertiser begins by giving Gemini strategic guidance: who the business wants to reach, which searches matter and what the ads should communicate. AI Max then performs matching, creative selection and landing-page routing. The forthcoming report shows how those decisions manifested in real user journeys.
The advertiser can then compare observed behavior with the original brief. If the system is attracting the wrong intent, producing weak messaging or routing users to undesirable pages, the brief and other campaign controls can be refined.
That is a more agentic campaign-management model: prompt, observe, correct and repeat.
Google is trying to answer the “black box” criticism before automation expands further
Advertisers have repeatedly asked for more transparency as Google Ads automates targeting and creative decisions. Performance improvements are difficult to trust when teams cannot explain which query triggered which message and destination.
Google’s wording reflects that concern. The company says the new interface is intended to help advertisers understand how customers interact with their businesses and validate the strategic value AI Max contributes to campaigns.
“Validate” is the important word. Google is not merely promising another optimization feature; it is promising evidence advertisers can use to determine whether the automation is doing what it claims.
The quality of that evidence will depend on the reporting details Google publishes later this year.
Google is also documenting how to test AI Max against Dynamic Search Ads
The reporting changes arrive while Google is moving advertisers away from Dynamic Search Ads and toward AI Max. Its updated Dynamic Search Ads documentation now includes explicit instructions for testing AI Max against an existing DSA campaign through experiments.
Google describes two approaches. Advertisers can use a custom experiment, upgrading the treatment campaign to AI Max while preserving the original campaign as the control, or use an AI Max experiment template where the campaign structure is eligible.
The documentation contains an important limitation: campaigns composed entirely of dynamic ad groups cannot use the templated AI Max experiment. Mixed campaigns can use the template, but only the non-DSA ad groups in the treatment arm are upgraded to AI Max while dynamic ad groups remain dynamic.
For 100% DSA campaigns, custom experiments provide the clearer path for a direct migration test.
Google has pushed the DSA auto-upgrade timeline to February 2027
The experiment guidance matters because Dynamic Search Ads are on a migration path. Google originally announced a faster transition but later extended the timeline after advertiser feedback.
The current help documentation says campaigns using DSA will begin automatically upgrading to AI Max in February 2027. That gives advertisers a window to test rather than waiting for an automatic conversion.
The experiment structure lets teams compare performance before making the transition permanent. If the AI Max treatment wins and the advertiser chooses to apply it, Google provides options to update the original campaign or convert the experiment into a new campaign, depending on the experiment type and configuration.
This makes experimentation part of the migration strategy rather than an optional analytical exercise.
The report could make AI Max experiments more diagnostically useful
A standard A/B test can establish whether a treatment produces better aggregate results. It does not necessarily explain why.
If the forthcoming query-to-creative-to-landing-page report can be used alongside AI Max experiments, advertisers could gain a much richer view of the mechanisms behind performance differences.
A treatment arm might outperform because AI Max discovers valuable searches the DSA campaign missed, because it adapts creative more effectively, because it routes users to better pages or because several of those mechanisms interact.
Google has not yet specified exactly how the new report will integrate with experiment reporting, so that use case remains to be confirmed. But the two product directions clearly complement each other: experiments measure incremental effect, while journey reporting is designed to expose the decisions inside the AI-powered path.
AI search advertising is becoming more native to conversational behavior
Google is simultaneously experimenting with how advertising appears inside AI-driven Search experiences. NetContentSEO recently reported that Google has tested sponsored links that visually resemble contextual citations inside AI Mode.
That observed UI test is separate from the official AI Max announcement, but both developments respond to the same underlying change: Search is becoming more conversational, and the advertising system has to adapt to journeys that no longer resemble a simple keyword followed by a static text ad.
AI Max is Google’s attempt to automate matching, messaging and destination selection for that environment. AI Brief gives the advertiser a natural-language steering layer, while the forthcoming report is intended to make the resulting journey visible.
As those systems converge, campaign management becomes less about manually constructing every route and more about setting constraints, evaluating outcomes and correcting the AI.
Italian language support matters beyond translation
The addition of Italian could look like a localization update, but natural-language campaign steering is unusually sensitive to language.
Brand tone, prohibited claims, audience nuance and commercial intent can be difficult to express precisely when teams are forced to brief an AI system in a language different from the one used by the campaign’s customers.
Allowing Italian advertisers to communicate directly in Italian reduces that translation layer. It also makes AI Brief more accessible to local marketing teams that understand the business deeply but may not work comfortably with English campaign instructions.
The value therefore comes not simply from translating interface text, but from letting the strategic input itself remain in the advertiser’s working language.
The campaign of the future may be defined by a brief and audited by a journey graph
Google Ads is moving toward a model in which advertisers specify strategic intent while AI handles an increasing share of execution. That shift only works if the platform provides both expressive controls and sufficient observability.
The September update advances both sides. AI Brief lets selected advertisers tell Gemini—in Italian and six other newly supported languages—what the business is, whom it wants to reach and how it wants to communicate. The planned reporting feature then promises to connect the user’s actual search term with the creative shown and the exact page reached.
Neither development is fully mature. AI Brief remains in closed beta, and Google has not yet published the availability or complete specification of the journey report. Advertisers should therefore avoid treating either as universally available today.
But the direction is clear. Google wants Search campaigns to become increasingly promptable while making the automated path more inspectable. If the reporting delivers the granularity promised, AI Max will not only decide more of the journey—it will finally give advertisers a better map of the journey it decided.