Google Ads: branded searches in AI Max
Google Ads is expanding AI Max with a long-awaited lever: controls for branded searches. According to current reports, selected advertisers are gaining access to “Branded Searches” controls within AI Max campaigns. That makes it possible to influence how ads serve on queries that include brand names—a move that reignites debate on cannibalization, budget efficiency, and clear account governance.
What the rollout means in practice
Until now, teams that wanted to keep AI Max away from brand-related traffic relied mainly on exclusion lists, parallel brand campaigns, and manual search term reviews. The new control aims to anchor that logic closer to the campaign level: advertisers should be able to define whether and how ads appear on brand-related queries. Google describes a phased rollout—not every account sees the option yet, which is typical for product stages with limited availability.
For performance leads, this mainly changes operations: instead of isolated workarounds, a native setting can be referenced consistently in playbooks, QA checklists, and quarterly reviews. Whether the control will cover all edge cases long term—modifiers, typos, generic brand-plus-product combinations—remains to be seen and should be tested in your own account.
Why branded queries are sensitive in AI Max
AI Max combines automation, signals, and delivery in a campaign type that relies heavily on machine matching. Brand queries often convert above average but also attract traffic that would reach the site without paid ads. When AI Max serves those queries, CPCs on already strong terms typically rise while incremental value becomes harder to measure.
- Risk of duplicate delivery alongside dedicated brand campaigns
- Blurred attribution between AI Max, Performance Max, and classic search campaigns
- Harder separation of protection vs. growth budgets in reporting
- Higher maintenance for negative lists when native controls are missing or incomplete
SEO and SEM teams should not view the launch only in the Ads interface. Organic brand visibility in SERPs, SERP features, and AI-powered surfaces provides the context in which paid decisions are judged. Clean brand vs. non-brand separation makes management reports easier to read and budget calls easier to defend.
Typical control logic and expectations
Even though Google’s short notice offers few UI details, many accounts align with three strategic directions known from earlier tests and industry reports: full relevance on all matching searches, explicit brand inclusions and exclusions, or focus on non-brand expansion. The native “Branded Searches” control is meant to address the gray zone where automated systems interpret brand intent without teams predefining every query pattern manually.
| Goal | Recommended monitoring |
|---|---|
| Brand protection | Compare impression share and CPC in parallel brand campaigns |
| Non-brand growth | Isolate new queries and CPA on non-brand terms |
| Governance | Document settings and timestamp changes |
Crucially, native controls must not replace search term analysis. Even with a campaign-level switch, search term reports, negative lists, and regular brand reviews remain mandatory because query landscapes stay dynamic and competitors, seasonality, or new products constantly create new patterns.
Operational workflow for affected accounts
If you already see the new option, run a structured test: capture the baseline with screenshots and exports, adjust one AI Max campaign with a clear hypothesis, and observe performance for at least one full conversion window. Keep brand campaigns unchanged or only adjust with documentation so effects stay attributable. If non-brand CPA drops unexpectedly or brand impressions in AI Max spike, revert the setting and involve support or your account team.
Impact on account structure and reporting
Agencies with many clients benefit from a standard approach: brand campaigns protect visibility and margin, AI Max focuses on prospecting, other automated formats follow their own rules. Rolling out branded search controls does not automatically reduce complexity, but it shifts it from scattered workarounds to a central, auditable place.
In dashboards that merge paid and organic, annotate when AI Max brand logic changed. That prevents ROAS, conversion rate, or organic traffic swings from being wrongly attributed to individual SEO measures. Finance and controlling also expect traceable separation of protection and growth budgets—native brand control supports that transparency if it works reliably.
Context in the Google Ads product direction
The step fits a pattern: Google scales automated campaigns but responds to feedback on control and transparency. After debates on Performance Max, Demand Gen, and AI Max, brand query control now moves to the foreground. For advertisers, it signals that cannibalization and attribution influence product decisions—not only community discussion.
The rollout remains selective. If you do not see the setting yet, keep maintaining exclusion lists and follow Google’s changelog communication. Early access is no guarantee of final behavior in a global release—interface copy, defaults, and interaction with other automation may still change before broad availability.
What teams should do now
First, check AI Max campaigns weekly for new settings and document changes in your team change log. When branded search controls are available, state hypotheses: should AI Max reduce brand queries, work with explicit brand lists, or expand non-brand? Define KPIs upfront—incremental conversions, brand impression share, CPA on isolated non-brand queries, and overlap with other campaign types.
Stakeholder communication should clarify this is a gradual product expansion. Expectation management prevents short test phases from being treated as permanent strategy. Those who test and document cleanly now are prepared when Google offers the control broadly—whether your account is already in the first wave or still waiting.
