Using AI in your search campaigns doesn’t mean surrendering control. When you turn on AI Max for asset generation and URL routing, you upgrade your campaign’s reach instead of replacing your strategy. But implementing this automation doesn’t mean you’re putting your campaigns on autopilot. Before you activate these tools, you need a plan to track where the system sends your traffic, protect your brand, and turn the new data into useful marketing intelligence.
The shift to automated search requires a new level of operational control. While AI Max reduces manual inputs, it increases overall campaign visibility if you guide it correctly. The challenge lies in making the algorithm work for your business goals without cannibalizing your existing efforts or violating brand guidelines. Marketers have to adapt to a system that writes its own ads and picks its own landing pages based on user queries.
That makes AI Max less of a feature adoption decision and more of a testing and measurement decision. The question is not whether automation improves campaign performance, but whether it creates incremental value, what it teaches you about demand, and how those learnings should influence the next media decision
Here’s what marketers need to know before activating AI Max.
Key takeaways
- AI Max is an optimization layer within Search campaigns, built around search term matching and asset optimization.
- Campaign readiness depends on strong conversion signals, adequate budget, reliable tracking, clear business objectives, and defined controls around brands, locations, URLs, and messaging.
- AI Max reporting can reveal useful search, creative, and landing-page signals that inform campaign decisions and broader audience strategy.
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What is AI Max?
AI Max is a suite of AI-driven targeting and creative features available in Google Search campaigns. Its two main components are search term matching and asset optimization.
Search term matching uses broad match, asset-based, landing page-based, and keywordless targeting technology to identify relevant searches connected to the campaign. Google uses information already available in your keywords, creative, and URLs to determine when an ad is eligible to appear.
Asset optimization guides how Google adapts the ad experience. Text customization can generate headlines and descriptions using information from your existing ads, landing pages, assets, and keywords. Final URL expansion can select a query-relevant landing page from your domain and pair that destination with customized copy. Final URL expansion requires text customization to be active.
Advertisers still define the campaign goal, bidding strategy, brand parameters, URLs, negative keywords, geographic requirements, and other controls. AI Max uses those inputs as the framework for its decisions.
How does AI Max change Search campaign management?
AI Max operates inside an existing Search campaign. Advertisers continue working with Search campaign structures, keywords, responsive search ads, bidding strategies, conversion goals, and landing pages. AI Max adds automated matching, text customization, and landing-page selection within that structure.
As platforms automate more execution, the marketer’s role shifts upstream. The advantage comes from deciding what signals the system receives, establishing the right guardrails, designing meaningful tests, and determining whether the outputs create real business value.
Your keywords, creative, landing pages, conversion data, and bidding strategy give Google information about the campaign’s objective and relevant demand. Your controls establish the areas where the system can operate. Negative keywords remain active with AI Max, and advertisers can use brand settings, URL controls, locations of interest, and messaging guidelines to shape campaign behavior.
This makes campaign governance part of your overall performance management. A search query can influence the ad copy a consumer sees and the page they reach, so those decisions need regular review.
That review should answer a few practical questions:
- Are the new queries relevant to the campaign objective?
- Are generated assets accurate and on brand?
- Are consumers reaching the appropriate pages?
- Is that traffic producing the business outcome the campaign was built to generate?
- Is the system creating incremental value, or simply capturing demand the campaign was already positioned to convert?
AI Max gives marketers additional ways to answer those questions inside Google Ads.
How do you manage AI Max?
Google naturally encourages advertisers to take advantage of the full AI Max suite, but that does not mean every advertiser needs to test every available feature at once.
At Amsive, we think about AI Max as a set of capabilities that can be tested based on the business problem you are trying to solve and the level of automation your organization is ready to support. Within Google’s available controls, that could mean starting with expanded search term matching while maintaining tighter control over creative and landing pages, or testing text customization before introducing Final URL Expansion.
The right starting point depends on the advertiser. A retailer with thousands of product pages may be comfortable giving Google more flexibility around landing-page selection. A financial institution with approved creative, product-specific rates, and strict disclosures may want significantly tighter controls.
A simple way to think about the progression is:
- Discover: Test whether expanded matching uncovers valuable demand beyond the existing keyword strategy.
- Create: Test automated text customization where brand and compliance requirements allow.
- Connect: Test Final URL Expansion where the site structure, content, tracking, and customer experience are ready to support dynamic landing-page selection.
- Scale: Combine capabilities once individual tests demonstrate value and the appropriate guardrails are in place.
The goal is not to turn on the most automation. It is to determine where automation creates incremental value without introducing unnecessary risk.
AI Max gives advertisers several settings that can be managed at the campaign or ad group level.
Search term matching
Search term matching is activated at the campaign level when AI Max is turned on. Advertisers can disable it for individual ad groups.
What to watch
Look closely at the incremental queries coming into the campaign. Are they genuinely relevant? Are they introducing new types of intent, or simply overlapping with queries you already capture? Are branded and non-brand dynamics changing? Watch conversion quality as well as volume, particularly when broader queries can generate leads that look good in-platform but are less valuable downstream.
For example, a home services advertiser may discover valuable searches around the way consumers describe a problem rather than the service itself. But broader matching could also introduce DIY, informational, employment, or out-of-service-area searches. Those patterns should inform negatives and future campaign structure.
Text customization
Text customization is managed at the campaign level. It uses existing campaign and website information to generate headlines and descriptions relevant to a consumer’s query.
What to watch
Review what Google is actually saying, not just how the assets perform. Look for claims that are technically pulled from approved content but do not make sense outside their original context, messaging that does not align with the intended audience or offer, and language that creates brand or compliance concerns.
This matters particularly in regulated industries. A financial institution, for example, may have a landing page advertising a specific APY with required disclosures. That does not necessarily mean the rate language should be dynamically incorporated into every ad or paired with a different product experience. If messaging requires strict legal or brand approval, maintaining tighter creative control may be the better test design.
Final URL expansion
Final URL expansion gives Google flexibility to choose a landing page it believes is more relevant to the consumer’s query. For sites with strong architecture and many useful destinations, that can create a more relevant experience. It also gives the platform considerably more influence over the customer journey.
What to watch
Review which URLs are actually receiving traffic and whether they make sense for acquisition. Look for outdated pages, expired promotions, servicing or login pages, informational content with no clear next step, and pages tied to products, rates, locations, or offers that do not match the consumer’s situation. Also validate tracking and URL parameters before and during the test.
Consider a bank with separate mortgage pages displaying different products or rates. Sending someone to a more specific mortgage page could improve relevance. Sending that same consumer to an outdated rate page, an existing-customer servicing page, or a product unavailable in their geography creates a very different outcome. URL exclusions and inclusions become an important part of the test design.
Brand controls
Brand inclusions can be applied at the campaign and ad group levels. Brand exclusions operate at the campaign level. These settings let advertisers define brand relationships that should influence matching.
URL controls
URL exclusions prevent specific pages from serving as landing pages. URL inclusions let advertisers direct AI Max toward additional approved pages.
Locations of interest
Locations of interest allow advertisers to act on geographic intent at the ad group level, including keywordless matches.
These settings should reflect the campaign’s actual business requirements. A regulated product, location-specific service, fixed promotional offer, or controlled landing-page experience may require tighter configuration.
What to watch for Brand, URL, and location controls
Look for places where Google’s definition of relevance and the business’s definition of eligibility are different. That could include brands you cannot advertise against, locations you cannot service, products unavailable in certain markets, or areas of the site that should not be part of paid acquisition.
The more flexibility you give the system, the more important these controls become. Start with the business rules you already know, then use what you observe during the test to refine them.
Readiness also extends beyond the campaign itself. Because AI Max can use landing-page content to inform matching, messaging, and routing, website structure and content quality effectively become part of the media strategy. Pages that are outdated, overly broad, or not intended for paid traffic can influence how the system operates unless they are deliberately controlled.
Responsive search ad pinning also deserves review. Google states that pinned RSA assets won’t be respected when final URL expansion selects a relevant URL. URL inclusions can also affect pinning. Campaigns that depend on specific pinned messaging should account for that behavior before activation.
How do you measure AI Max performance?
AI Max reporting gives marketers several views into how the system is working.
Start by separating platform performance from business impact. A stronger CPA or ROAS can be encouraging, but it does not automatically mean AI Max created incremental demand. Evaluate the treatment in the context of total Search performance, branded and non-brand behavior, conversion mix, and whether conversions shifted from existing campaign activity.
Search term reporting
The search terms report can identify AI Max as the match type for incremental queries and show whether the match came through broad match expansion or keywordless matching.
Google also provides a view that connects the search term, headline, and URL, giving marketers context around the experience served for a particular query.
Use this report to review query quality and spot patterns that require new negative keywords, revised controls, or additional campaign coverage.
Landing-page reporting
The Landing pages report includes a “Selected by” field showing when AI Max chose the destination.
Review conversion performance and engagement by destination, then inspect pages receiving unexpected traffic. URL exclusions can remove destinations that don’t belong in the campaign.
Asset reporting
Asset reports show performance information for assets generated and optimized through AI Max. This gives teams a way to see which automated creative is receiving investment and producing conversions.
Reviewing this data can also surface messaging themes that deserve further testing in manually developed ads, landing pages, and creative.
Operational impact
Campaign performance tells part of the story. Management requirements matter, too.
Track how frequently your team needs to add negatives, correct URL routing, remove generated assets, or revise campaign controls. Repeated corrections can point to a campaign structure, site architecture, or governance issue that needs attention.
Automation should produce useful information for the next campaign decision, not just a better optimization score inside the platform. Capture what the test reveals about query behavior, creative, landing pages, audience needs, and campaign structure so those learnings can influence future media strategy.
When should you test AI Max?
Do not start by asking whether you should turn on AI Max. Start by defining what you are trying to learn. A useful test might ask whether AI Max can uncover incremental demand, improve conversion efficiency, identify valuable queries outside the existing keyword structure, or surface new messaging and landing-page opportunities.
Google provides a dedicated AI Max experiment for Search campaigns. The experiment can split traffic within the current campaign, allocating 50% to the existing campaign settings and 50% to the AI Max treatment. The AI Max treatment activates search term matching and asset optimization by default, and advertisers can adjust those settings within the experiment.
Start with a campaign that has a defined conversion objective, stable tracking, suitable bidding, and enough budget to support the test.
Set the success criteria before launch. Focus the evaluation on business outcomes such as conversion volume, conversion value, CPA, or ROAS, then review the search terms, generated assets, and landing pages responsible for those outcomes.
Also define what would count as incremental value. Review whether gains are coming from new demand, broader non-brand coverage, different query behavior, or simply a redistribution of conversions the account was already capturing.
Avoid assigning a fixed “learning period” to AI Max. Google’s general experiment guidance recommends allowing an experiment to run for at least four to six weeks when the reported result remains undetermined. Campaign volume and available data can affect the time required to reach a useful conclusion.
The experiment should answer a specific campaign question. Document that question before launch so the team knows what evidence will support the next decision.
A practical framework is: hypothesis → test → business outcome → incrementality → learning → next action. That keeps AI Max testing focused on what the marketer learns, not simply whether the platform reports a lift.
What does AI Max testing look like by industry?
There is no single AI Max configuration that makes sense for every advertiser. Industry regulations, website structure, customer journeys, product complexity, and the way consumers search should all influence which capabilities you test and how much flexibility you give the system.
Here are a few examples of what that can look like in practice.
Financial services and credit unions
Imagine a credit union advertising checking accounts, auto loans, mortgages, and certificates, each with different rates, eligibility requirements, disclosures, and landing pages.
What we might test
Start with search term matching to identify consumer needs that the existing keyword structure may not capture. For example, searches around financing a first car or comparing certificate returns may reveal valuable intent without immediately introducing automated creative or landing-page selection.
What we’d be careful with
Text customization and Final URL Expansion may need tighter controls. If rates, promotional offers, eligibility language, or required disclosures vary by product or page, dynamically combining messaging and destinations can introduce compliance or customer-experience risk. Approved messaging may be a business requirement, not simply a creative preference.
Health insurance
Health insurance searches can change considerably based on coverage needs, life events, geography, enrollment timing, plan type, and eligibility.
What we might test
Use expanded matching to learn how consumers are describing their coverage needs beyond the existing keyword set, while keeping approved creative and landing pages controlled initially.
What we’d be careful with
A query can appear highly relevant while the available plan is not. Geography, eligibility, enrollment periods, plan availability, and regulated messaging all matter. This is a good example of a vertical where discovering new search demand may be valuable even if the advertiser is not ready to automate the entire experience.
Auto, home, and other insurance
Someone searching for insurance may describe the product, the asset they need to insure, a life event, a coverage question, or simply a desire to lower their rate.
What we might test
Search term matching can uncover long-tail intent such as consumers looking to bundle products or insure a specific type of property or vehicle. Those queries can become inputs for future keyword, audience, and content strategies.
What we’d be careful with
Separate research behavior from quote intent and monitor lead quality downstream. Also watch state-specific availability and make sure Final URL Expansion cannot route prospects into policy servicing or existing-customer experiences.
Education
Prospective students rarely search only for the exact name of a degree. They may search around career outcomes, program formats, degree levels, cost, location, prerequisites, or how quickly they can complete a program.
What we might test
Search term matching could uncover searches such as “online degree for working adults” or career-oriented queries that do not map directly to an existing program keyword. Final URL Expansion could then be tested separately to determine whether Google can connect those searches to more relevant program pages.
What we’d be careful with
Make sure the destination represents a program that is actually offered in that format, geography, or enrollment period. Old program pages and content pages with no clear prospective-student journey should be excluded.
Retail and eCommerce
A retailer may have thousands of products and category pages, making it difficult for a manually managed keyword and landing-page strategy to account for every long-tail search.
What we might test
This can be a stronger candidate for combining search term matching with Final URL Expansion. A highly specific search could potentially be matched with a more relevant category or product page than the advertiser would have selected manually.
What we’d be careful with
Inventory and site quality become critical. Watch for discontinued products, out-of-stock items, expired promotional pages, weak category experiences, and overlap with Shopping or Performance Max. More conversions inside the Search campaign do not necessarily mean more incremental conversions for the business.
Home services
Consumers often search for the problem before they know the service they need. Someone may search for “water pooling around furnace” rather than “HVAC repair,” for example.
What we might test
Search term matching can be particularly useful for identifying problem-based and urgency-based language that traditional service keywords miss. Locations of interest can also help when geographic intent is important.
What we’d be careful with
Serviceability. Expanded matching can find a perfectly relevant lead in a ZIP code the business does not serve or for a service the location does not provide. Watch geography, lead quality, DIY and informational searches, and employment-related queries closely.
Healthcare
A patient may search using symptoms or everyday language rather than the terminology a health system uses to organize specialties and services.
What we might test
Carefully controlled search term matching can help identify the language consumers use and uncover gaps between consumer search behavior and existing service-line keyword strategies.
What we’d be careful with
Healthcare requires a much more conservative approach to automation. Sensitive intent, messaging accuracy, provider and location availability, and the distinction between informational content and an appropriate care destination all matter. Automated creative or URL selection may not be appropriate for every service line.
Travel and hospitality
Travel searches can combine destination, property type, amenities, dates, experiences, proximity to attractions, and traveler needs in thousands of different ways.
What we might test
Search term matching can uncover long-tail intent around experiences or amenities, while Final URL Expansion may help connect a traveler to a more relevant property, destination, package, or experience page.
What we’d be careful with
Availability and accuracy. Seasonal packages, expired offers, unavailable properties, outdated destination content, or pages that cannot support the consumer’s actual booking need can quickly undermine the benefit of a more relevant match.
The common thread across these examples is that AI Max does not have to be one test. Search term matching, text customization, Final URL Expansion, and the available controls can be evaluated based on the specific question the advertiser is trying to answer.
For some advertisers, the right first test may be simply giving Google more freedom to find demand. For others, it may be testing whether automation can create a better message or customer journey. The right level of automation is the one that creates measurable value while still respecting the realities of the business.
How can AI Max search data inform audience strategy?
Search queries capture the language people use when they’re actively trying to solve a problem, evaluate an option, or find a product or service.
AI Max adds another layer of context around those queries. Marketers can see how Google matched the search, which message it served, and which landing page it selected. Patterns across those interactions can reveal recurring consumer needs, terminology, geographic intent, product interests, and points of confusion.
Those signals should feed the marketing work happening outside the Search campaign.
That should work in both directions. Search behavior can create hypotheses for paid social, programmatic, CTV, CRM, creative, and site content, while first-party and audience insights from those channels should inform the hypotheses marketers bring back into Search. The objective is a closed learning loop, not a Search-only optimization cycle.
Repeated query themes can inform audience hypotheses, creative briefs, website content, paid media messaging, email programs, and direct mail. A consumer need that consistently appears in Search can become a useful input for how the brand speaks to that audience across the rest of its marketing.
The value comes from turning search behavior into usable marketing intelligence. Each test should leave the team with a stronger understanding of the audience and the messages that matter to them.
FAQs
Is AI Max a separate Google Ads campaign type?
No. AI Max is an optimization layer activated within an existing Search campaign.
How does AI Max work within Search campaigns?
AI Max centers on search term matching and asset optimization. Search term matching uses broad match and keywordless technologies to identify relevant queries. Asset optimization includes text customization and final URL expansion.
Can advertisers control individual AI Max features?
Yes. Search term matching can be controlled at the ad group level after AI Max is activated for the campaign. Text customization and final URL expansion are campaign-level settings and can be managed individually.
How long should an AI Max test run?
Use the experiment’s reported result and available data to determine the testing window. If the result remains undetermined, Google recommends allowing experiments at least four to six weeks to collect additional data.
What reporting is available for AI Max?
Google provides AI Max information across search term, keyword, landing page, and asset reports. Advertisers can review matching sources, queries, headlines, selected URLs, and asset performance.
How do URL exclusions work?
URL exclusions operate at the campaign level and prevent selected pages from serving as landing pages. URL inclusions are available at the ad group level to give AI Max additional approved destinations.
Build AI Max around controlled testing
AI Max expands what Google can automate inside a Search campaign. It can identify relevant queries, generate customized text, and select landing pages based on search intent. Those capabilities make campaign setup, governance, tracking, and reporting central to performance.
Marketers still own the inputs that shape the campaign. Conversion goals, bidding, investment, landing pages, brand requirements, negative keywords, URL rules, and measurement all determine the environment AI Max operates within.
Use the first test to answer a specific business question. Define what you expect AI Max to improve, establish the guardrails before launch, measure whether the value is incremental, and document what the system teaches you about audiences, messaging, landing pages, and demand.
As AI takes on a larger role in Search execution, the advantage will come less from simply adopting automation and more from how well marketers test and govern it. The goal is not only to make AI Max perform better. It is to make every test improve the intelligence behind the next media decision.
Learn more about three AI-optimized frameworks for improve your Google campaigns, or let’s talk about achieving more for your marketing—and your business.
