# Google Adds AI Max Testing and Planning Tools > Source: > Published: 2026-08-20 18:09:08+00:00 # Google Adds AI Max Testing and Planning Tools Google announced new AI Max testing and planning tools for Search campaigns on Aug. 20, including a September rollout of multi-campaign A/B tests for budget and ROI targets. The update also adds brand and location controls to AI Max experiments and expands Performance Planner with one-click application of suggested bidding and budget changes. Google announced new testing and planning features for **AI Max** in Search Ads, adding multi-campaign experiments, brand and location controls, and expanded Performance Planner recommendations. According to Google's Aug. 20 product post, the multi-campaign test capability is scheduled to roll out in September. The new experiment format enables advertisers to test different budgets and ROI targets across multiple Search campaigns in a single A/B test. Google wrote: "Building on the one-click experiments in AI Max, we're now introducing a way for you to test different budgets and ROI targets across multiple Search campaigns in a single A/B test." ### Experiment controls and planning changes Google also added brand and location controls to AI Max experiments. The company described the controls as a way for advertisers using those restrictions to test AI Max while retaining their existing guardrails. Separately, Google's **Performance Planner** can now model how proposed bidding or budget-target changes could affect existing campaign performance. The product post states that advertisers can apply its suggested changes to campaigns in one click. PYMNTS, which reported on the announcement, described the release as a set of AI tools intended to help businesses scale Search campaigns. Its report also noted that the Google post promoted the company's upcoming Rethink 2026 event. ### What changes for campaign measurement For paid-search practitioners, the material change is the ability to evaluate budget and target adjustments across a portfolio of Search campaigns rather than relying solely on campaign-level experiments. Controlled testing is particularly relevant where automated bidding changes can alter conversion volume, spend distribution, and return metrics simultaneously. As with comparable advertising-platform automation features, teams assessing the tools will need to define success metrics before testing, maintain sufficiently long test windows for conversion lag, and separate incremental lift from changes caused by seasonality or creative updates. Google's announcement does not provide performance benchmarks, eligibility criteria, or details on how the multi-campaign test methodology handles budget reallocation. ## Key Points - 1Google's September AI Max update introduces one A/B test for budget and ROI targets across multiple Search campaigns. - 2New brand and location controls let advertisers test AI Max while retaining specified campaign guardrails, according to Google's product post. - 3Portfolio-level ad experiments can improve measurement, but comparable automation tests require careful controls for conversion lag, seasonality, and budget redistribution. ## Scoring Rationale The update adds practical experimentation and planning capabilities to Google's widely used Search Ads platform. It is relevant to marketing data teams and ad-tech practitioners, although the announcement includes no new model, benchmark, or broad platform architecture change. ## Sources Primary source and supporting public references used for this report. Practice with real Ad Tech data 90 SQL & Python problems · 15 industry datasets [Active Search Campaigns by BudgetEasy](/problems/sql/active-search-campaigns-by-budget) [High CPC Clicks & Poor Landing PagesMedium](/problems/sql/high-cpc-clicks-poor-landing-page) [Campaign ROAS by Attribution ModelHard](/problems/sql/campaign-roas-by-attribution-model) 250 free problems · No credit card [See all Ad Tech problems](/problems/datasets/adtech)