Google Ads Launches New Search and AI Max Experimentation Tools

Google Ads is giving advertisers greater control over campaign testing with a suite of new experimentation and planning tools designed to reduce guesswork and improve performance outcomes before changes go live.

Announced on August 24, 2026, the updates introduce multi-campaign testing capabilities, expanded AI Max experiment controls, and a streamlined Performance Planner workflow. Some tools are already available while others begin rolling out in September 2026. For advertisers who want to understand how these tools fit into a broader paid search strategy, it helps to first consider the key differences between SEO and PPC and when each approach delivers the most value.

Multi-Campaign Testing, AI Max Controls, and Smarter Planning

Multi-campaign testing arrives in September

Starting in September, advertisers will be able to test budget and return-on-investment (ROI) target changes across multiple Search campaigns within a single A/B experiment. This marks a meaningful expansion from the one-click experiments Google previously introduced for AI Max — which were limited to individual campaign changes.

The new capability addresses a common pain point for advertisers managing large portfolios. Rather than adjusting each campaign independently and hoping the results translate across the account, advertisers can now test a unified strategy against a control group before committing to it.

For example, an advertiser considering a significant budget increase can apply that test across a cluster of Search campaigns simultaneously. ROI targets can also be folded into the experiment, giving decision-makers a clearer picture of how scaling affects their bottom line.

This approach matters because budget and bidding decisions rarely exist in isolation. Performance in one campaign can ripple across an account, and single-campaign testing has historically made it difficult to evaluate those broader effects with confidence. The September rollout will be worth watching closely — particularly for larger accounts where portfolio-level budget decisions carry significant financial weight.

AI Max experiments expand brand and location controls

Google is also addressing a long-standing limitation in how advertisers test AI Max for Search campaigns. Advertisers can now run AI Max experiments while keeping brand and location settings enabled — controls that previously had to be removed or adjusted to run a valid experiment.

That restriction created a real problem for advertisers whose campaigns depend on geographic targeting or brand safety guardrails. Removing those settings to test AI Max meant the experiment no longer reflected how the campaign would actually operate after launch, making the results less useful in practice.

The update closes that gap. Advertisers that rely on brand controls or geographic restrictions can now evaluate AI Max performance under conditions that closely mirror their intended campaign setup. Test results should be more actionable as a result.

This is particularly relevant as AI Max continues to evolve as a tool for finding additional conversion opportunities beyond standard keyword targeting. Advertisers considering AI Max adoption can now run a more realistic trial without dismantling the safeguards already built into their campaigns. Understanding the full landscape of Google tools available to help grow your business can provide useful context for evaluating where AI Max fits within a wider campaign strategy.

Performance Planner gets one-click implementation

The third update streamlines how advertisers move from forecasting a campaign change to actually applying it. Performance Planner can now show how adjustments to bidding or budget targets may affect existing campaign performance, and advertisers can apply those suggested changes directly with a single click.

Before applying any plan, advertisers can review proposed changes at the campaign level and deselect specific campaigns they want to exclude. Changes applied through Performance Planner can also be monitored and reversed through the Bulk Actions section in Google Ads — providing a safety net if results don't match expectations.

The update is designed to shorten the distance between planning and execution. That efficiency is valuable in fast-moving campaigns where delayed implementation can mean missed opportunities.

However, the convenience of one-click application raises the stakes on review. Applying forecasted changes without scrutinising the underlying assumptions could lead to unintended budget shifts or bidding changes across multiple campaigns at once. The tool is more powerful, but that power cuts both ways.

What These Changes Mean for Advertisers Navigating Automation

Google Ads has steadily expanded how much automation influences Search campaign management — from Smart Bidding to Performance Max to AI Max. Each wave of automation introduces efficiency but also reduces direct advertiser control over individual decisions.

The new experimentation tools represent Google's acknowledgment that advertisers need reliable ways to validate automated recommendations using their own data before adopting them at scale. As one Search Engine Land analysis noted, more experimentation capabilities give advertisers a better way to evaluate those changes using their own performance data before applying them more broadly.

That validation layer is becoming increasingly important. Advertisers who can confidently test Google's automated features within their specific account context are better positioned to decide which changes to adopt — and where existing manual strategies still outperform. For those looking to deepen their understanding of how Google's paid search intelligence has developed over time, a closer look at the evolution of Google AdWords intelligence and what it means for advertisers offers valuable background.

How Advertisers Can Put This Into Practice

The practical implications of these updates vary depending on account size, campaign complexity, and how heavily an advertiser currently relies on automation. The following actions are worth prioritising:

• Plan ahead for September. Identify Search campaigns where budget or ROI target changes have been under consideration and prepare to use multi-campaign experiments as a structured testing vehicle rather than making changes without a baseline to measure against.

• Audit AI Max eligibility. Advertisers who previously avoided AI Max testing because of brand or location control requirements should revisit that decision now that those guardrails can remain in place during experiments.

• Review before you click. The one-click Performance Planner feature is a time-saver, but treat it as a starting point for review rather than a final answer — examine proposed changes at the campaign level before applying them across an account.

The thread connecting all three updates is the same: Google is building more structured ways to test before committing. For advertisers, the discipline of actually using those tools — rather than skipping straight to implementation — is where the real advantage lies.