Google announced two AI Max updates on September 23, 2026: a seven-language expansion for the closed beta of AI Brief and a new reporting experience connecting search terms, headlines and landing pages. Google initially said additional availability details would follow later in 2026. Its current documentation now describes the reporting workflow in product.
The reporting change is the more important update for paid media teams. Google originally said it would share more details and availability later in 2026. Its current Google Ads Help documentation now describes the in-product view as Search terms and ad combinations, while the Google Ads API documentation exposes the same query, headline and landing-page combination programmatically.
That does not make AI Max fully transparent. It does make it much easier to see where the automation made a poor decision.
What changed after Google’s September 23 announcement
| Update | Current status | What marketers get |
|---|---|---|
| AI Brief language expansion | Closed beta | Dutch, French, German, Italian, Japanese, Portuguese and Spanish join the beta for advertisers that have access. |
| Search terms and ad combinations | Documented in Google Ads Help | A combined view of search term, headline, landing page, campaign and ad group. |
| Dedicated API view | Documented in Google Ads API | Technical teams can query search term, headline and landing-page combinations and associated performance metrics. |
The distinction matters. AI Brief is still a closed beta, so the seven-language expansion does not mean every advertiser can switch it on. The reporting workflow is now documented in Google’s current Help and API material, which gives teams a concrete process to audit AI Max activity.
This comes as AI Max for Search campaigns takes on a larger role inside Search. The more decisions Google makes about matching, text and destinations, the more valuable it becomes to inspect those decisions together.
Why the new reporting view fixes a real blind spot
AI Max can expand beyond an advertiser’s keyword list, create or select text through text customization, and use final URL expansion to choose a destination that Google considers relevant. Each feature can help a campaign find additional demand. Each also creates another place where automation can drift away from commercial intent.
Before the combined view, teams could inspect search terms, assets and landing pages separately. That often made diagnosis slower than it needed to be. A campaign could look healthy in aggregate while the underlying combination was weak: a relevant query paired with a vague headline, or a strong query sent to a blog post instead of a conversion page.
This is where Google AI Max reporting becomes useful. The dedicated Search terms and ad combinations view makes those failures much easier to catch. If query expansion is the part you are trying to understand, our guide to Google Ads keyword match types explains why exact, phrase and broad match already operate with more semantic latitude than their labels suggest.
Google AI Max reporting is useful for diagnosis, not reconciliation
The API documentation calls ai_max_search_term_ad_combination_view the most granular AI Max report. It exposes the search term, headline and landing page used for the expansion, along with performance metrics. For large accounts, that makes automated audits much more practical.
There are two limits worth keeping front and center.
First, Google says the date is the only segment that can be selected directly on this view. Second, the combination view overlaps with the standard search term view. The same traffic can appear in both, so Google explicitly warns advertisers not to add the metrics together.
Privacy thresholds create another gap. Low-volume search terms can be omitted even though their clicks still appear in campaign totals. In other words, Google AI Max reporting is an auditing surface, not a complete financial ledger.
| Business question | Can the report answer it? | What else you need |
|---|---|---|
| Was the search relevant to the product? | Mostly | Query, headline and landing-page review |
| Did the lead become qualified? | No | CRM stages and offline conversion data |
| Did AI Max create incremental demand? | No | A controlled experiment or credible baseline |
| Should the campaign get more budget? | No | Pipeline economics, CAC or ROAS targets |
| Did every AI Max query appear? | No | Allowance for privacy thresholds and hidden terms |
What the combined view changes for B2B SaaS teams
For B2B SaaS, the useful question is rarely whether Google generated a conversion. It is whether the query, promise and destination attracted someone who could realistically become a customer.
Query quality comes first. Student, job-seeker, free-tool, consumer and research-only searches can all look active without being commercially useful. When a weak theme starts appearing repeatedly, a negative keyword may be the cleanest fix. Our negative keywords and ad targeting guide covers how to structure those exclusions without blocking useful demand.
Headline fit comes next. If the query is commercially sound but the headline overstates the product, uses the wrong category language or makes a claim the company would not approve manually, the problem is creative governance rather than targeting.
Landing-page selection can be the quiet failure. If final URL expansion repeatedly routes valuable traffic to a login page, generic homepage, outdated feature page or low-intent article, URL exclusions can be faster than trying to solve the issue through keywords.
The new view makes those three checks easier because the evidence sits in one place.
A practical weekly Google AI Max reporting review
- Start with the combined view. Review search term, headline and landing page together rather than treating them as separate reports.
- Tag weak intent. Group commercially poor themes before they scale, then decide whether they need exact, phrase or broad negative coverage.
- Check AI-created messaging. Look for claims that are vague, off-brand, misleading or too aggressive for the market.
- Audit destination choice. Exclude pages that repeatedly attract spend without supporting the conversion goal.
- Join campaign data to pipeline quality. Compare AI Max traffic with qualified lead rate, opportunity creation, pipeline value and revenue before increasing budget.
That last step is the one Google Ads cannot do for you automatically. Our guide to Google Ads automation makes the same point: automation is only as useful as the business signal it is optimizing toward. For a broader account-level review, use our Google Ads audit checklist to check wasted spend, conversion tracking and campaign structure alongside AI Max activity.
Better visibility still does not prove incrementality
Seeing the query, headline and page together tells you more about what happened inside the campaign. It does not prove that AI Max created demand you would not have captured otherwise.
That requires testing. Google’s recent AI Max testing tools move closer to that question by letting advertisers compare automation, budgets and ROI targets under controlled conditions. The reporting view tells you where the system made decisions. Experiments are what help you judge whether those decisions created additional business value.
This distinction matters because aggregate Google Ads performance can improve while lead quality deteriorates. A lower CPA is not a win if sales rejects more of the leads.
Also announced: AI Brief expands to seven languages
Google says AI Brief lets advertisers guide AI Max with written context about the business, audience and key messaging. The September update added Dutch, French, German, Italian, Japanese, Portuguese and Spanish, but AI Brief remains a closed beta, so this is not broad availability.
Google is separately changing Search language targeting. Its language targeting documentation says campaign language settings are no longer required for Search starting in September 2026, with Google using ad language, search-term language and user-language signals instead. That change is separate from AI Brief.
What marketing teams should watch next
- Broader AI Brief access: the seven-language expansion remains a closed beta, so access is still limited.
- Reporting consistency across accounts: Google documents the workflow, but the September launch post did not give one universal account rollout date.
- More API flexibility: the dedicated combination view is useful, but direct segmentation remains limited compared with broader campaign reporting.
- Privacy-threshold effects: hidden queries mean the reporting view should not be treated as a complete record of every AI Max search.
- Competitive transparency: our comparison of Google and Microsoft AI Max shows that reporting visibility is becoming a meaningful point of difference between the platforms.
OneMetrik Takeaway
Google AI Max reporting is a useful improvement because it exposes more of the decision chain behind an automated Search interaction: query, message and destination.
The temptation will be to treat better reporting as proof that AI Max itself is better. It is not. The report gives advertisers a better microscope. It does not tell them whether the traffic became qualified pipeline or whether the campaign created incremental demand.
For B2B SaaS teams, the right use is diagnostic. Find weak queries, catch mismatched headlines, exclude poor landing pages and identify where the automation is drifting. Scale only after CRM quality, pipeline value, CAC and controlled testing support the decision.