How Google runs ads in AI Overviews

AI Overviews sit on top of millions of Google search results and answer complex questions before users scroll. Google now monetizes that placement by inserting ads around and inside the AI box, yet offers advertisers limited visibility.

You do not get a new toggle called AI Overview placement. You get a different layout, new query patterns, and a reporting gap. This article explains how Google runs ads in AI Overviews, which campaigns qualify, how to measure performance, and how to connect this with your GEO and SEO strategy.

How AI Overviews work and when ads can show

Ads in AI Overviews ride on the standard Google Ads auction. AI Overviews appear on complex, answer-seeking queries, and ads can show above, below, or inside the AI box when commercial intent and quality thresholds are met. You cannot force these placements, but you can design campaigns that are eligible when the surface appears.

AI Overviews now appear on a meaningful slice of searches. Munro Agency reports that in 2025 they showed on more than 30 percent of searches in English-speaking markets such as the US and UK. Google also announced plans to reach more than one billion users by the end of 2024.

Google documentation shows that AI Overviews trigger on questions where users compare options or solve multi-step problems. They appear less on short “buy now” terms and more on questions like “best CRM for startups using Google Workspace.”

Google Ads Help states that when AI Overviews appear, search and Performance Max campaigns can show ads above, inside, or below the AI box. The same auction logic applies, with ad rank driven by bid, relevance, and quality.

What actually needs to be true for an AI Overview ad to show

Think about eligibility as a stacked set of conditions:

1. The query must trigger an AI Overview
2. The query must show commercial intent
3. Eligible campaigns must exist, usually search or Performance Max with AI-driven targeting
4. Your ad and landing page must meet quality thresholds
5. Smart bidding must be competitive for that user

Google VP Vidhya Srinivasan explains that Google can read informational queries and identify when connecting a user to a product is the logical next step. That is why ads appear even when the query starts as research, not purchase.

For advertisers, treat AI Overview impressions as upper and mid funnel traffic that still needs nurturing, clean targeting, and measurement beyond last click metrics.

Where ads appear in AI Overviews on the page

Google can place ads above the AI Overview, inside the AI box, or below it next to organic listings. Most impressions show below the AI box, though a consistent share still appears above it, which preserves top-of-page visibility.

GrowByData tracked retail categories and found AI Overviews increased from 5.2 percent of SERPs in January 2025 to 13.5 percent in June 2025. In the same data, most ads appeared below the AI box, while 18 to 20 percent appeared above it.

Google documents three core placements:

• Above the AI Overview as Top Ads
• Below the AI Overview between the AI box and organic listings
• Within the AI Overview as sponsored cards

How the layout changes user behavior

Several patterns show up across studies:

• Users get answers without clicking, which increases zero-click behavior
• A study cited by Lunio reported a 34.5 percent reduction in clicks when AI Overviews appeared
• Italian publishers reported up to 80 percent click declines on certain queries

Users often read the AI answer first, skim cited sources, and only then scan ads and organic listings. Above box ads still get attention, but they compete with the AI response itself.

What this layout means for your SERP strategy

Practical implications for teams:

• Paid and organic now operate inside one AI-centered experience
• If AI Overviews push your organic listing down while a competitor wins an above box ad, you lose attention even with similar rankings
• If you win an ad near the AI box and your page is also cited as a source, you gain extra visibility in a smaller viewport

Tie this directly to your GEO and SEO work. If you already invest in AI SEO and local AI SEO, design paid programs that reinforce the same entity footprint.

Which campaigns and settings make you eligible for AI Overview ads

There is no AI Overview checkbox in Google Ads. Eligibility flows through search and Performance Max campaigns that use AI-powered targeting, broad match, quality creative, and smart bidding. Accounts locked into exact match only and manual bidding typically see less AI Overview inventory.

Google Ads Help and agency analyses agree on the pattern. Ads in AI Overviews come from existing campaigns. Google also recommends AI-driven targeting, broad match, and automated bidding.

Core campaign types and their role

Here is a simple view of which campaigns matter.

Search plus Performance Max remains the practical core. AI-first campaign types will mature, but most advertisers need stronger governance before scaling them.

Practical eligibility checklist for your account

To increase eligibility, focus on:

1. Campaigns
   • Maintain search coverage across question-based and long tail queries
   • Use Performance Max where product feeds or lead flows are strong
2. Targeting
   • Use broad match for discovery-oriented questions
   • Organize ad groups around topics and intent
3. Bidding
   • Use target CPA or target ROAS with enough volume
   • Set targets that allow exploration on early-stage queries
4. Creative
   • Write ads that mirror natural language questions
   • Match landing pages to guides, comparisons, or calculators
5. Policy and category
   • Check whether your vertical is restricted under YMYL rules
   • If restricted, prioritize GEO and organic citations instead of chasing unavailable inventory

“As client programs evolve, eligibility improves fastest when campaigns are structured around real questions users ask, not only brand or product names.”
Brittany Charles, SVP, Client Services

Launchcodex often maps client campaigns to AI Overview style queries, then introduces one or two test campaigns using broad match and smart bidding to learn safely.

How to measure AI Overview ad performance with limited reporting

Google does not break out AI Overview placements in Google Ads or Search Console. You will not see AI Overview as a row in your reports. To understand performance, combine SERP tracking, controlled experiments, and analytics segments tied to pages and queries that often trigger AI Overviews.

GrowByData highlights this reporting gap clearly. Google provides no placement-level metrics for AI Overviews. Search Console rolls AI Overviews and AI Mode into the standard Web search type.

That makes internal measurement more important, not less.

Build a simple measurement framework

A practical framework looks like this:

1. Identify AI Overview queries
   • Use SERP tools or manual checks to build a query list
   • Group queries by intent and product line
2. Map queries to campaigns
   • Connect each query to the ad groups that usually capture it
   • Map to organic and paid landing pages
3. Create analytics segments
   • Segment traffic by landing pages tied to AI Overview queries
   • Track conversion rate and assisted conversions
4. Run controlled tests
   • Increase investment on selected segments
   • Use geography or time-based controls when possible
5. Overlay external SERP data
   • Monitor how often AI Overviews appear for your target queries
   • Compare AI Overview presence to conversion shifts

The goal is to answer whether AI Overview friendly campaigns improve pipeline and revenue for affected queries, not to isolate every single click.

Watch for invalid traffic and noise

Imperva research cited by Lunio suggests bots represent more than half of internet traffic. New AI surfaces can change click quality.

Reduce risk by:

• Enabling invalid traffic protection tools
• Watching for click spikes without engagement
• Excluding suspicious IPs or placements when possible
• Scaling only after clean, repeated lifts

“For tests like this, we pair campaign changes with warehouse views so teams can see assisted revenue and not overreact to short-term click swings.”
Derick Do, Co-Founder and Chief Product Officer

How AI Overviews change the mix of SEO, GEO, and paid search

AI Overviews compress the SERP, reduce organic clicks, and blur the lines between organic and paid. Winning means treating SEO, GEO, and paid search as one system that protects total demand, not separate channels that argue over attribution.

Studies cited by Lunio and Ahrefs show that when AI Overviews appear, clicks can drop by more than one-third. Italian publisher groups reported much larger drops on certain categories and raised concerns with regulators.

From a brand perspective, three shifts matter:

• Fewer organic clicks even with strong rankings
• More zero-click behavior as users read answers in Google
• New ad units that can offset lost visibility for prepared teams

How GEO and AI Overviews overlap

GEO focuses on making your entities and pages easy for models to cite. AI Overviews use similar signals.

That means:

• Pages optimized for AI citations often become AI Overview sources
• Strong entity markup supports both ad relevance and organic trust
• When your page is cited and your ad appears near the AI box, your brand gains more page presence

This connects directly with local and multi-location strategies, where clean profiles and structured data support both GEO and paid performance.

When shifting spend makes sense

You do not need a full budget shift. Instead:

• Protect high-intent core terms
• Allocate a small, defined budget slice to AI Overview-friendly queries
• Measure total pipeline impact, not only CPA

Brands in restricted YMYL categories may not see AI Overview ad inventory at all. Here, the priority is understanding how AI Overviews rewrite snippets and how to earn citations through content quality and clarity.

A practical playbook to test AI Overview ads in your account

You can learn a lot with a focused six-week test. Target AI Overview queries, use smart bidding, and rely on controlled experiments. Define success before you launch and evaluate performance using total conversions and pipeline, not only clicks.

Here is a pragmatic test structure.

Step one: define the test scope

1. Choose one or two products with stable paid search performance
2. Build a list of 50 to 150 queries with consistent AI Overviews
3. Select specific markets so you can compare on and off test regions

Step two: design AI Overview-friendly campaigns

1. Create or refine a search campaign using broad match on question-based themes
2. Group ad sets by user intent, not only keywords
3. Write ad copy that acknowledges the question and offers a next step
4. Send users to guides, comparison pages, or calculators

If Performance Max is already active, isolate one asset group for AI Overview themes.

Step three: set smart bidding and budgets

1. Use target CPA or target ROAS with enough conversion history
2. Set targets close to your baseline, then widen slightly for exploration
3. Allocate 10 to 20 percent of non non-brand search budget for the test

Step four: instrument measurement

1. Tag all campaigns and pages tied to the test
2. Create analytics segments for test landing pages
3. Track primary and assisted conversions, plus engaged sessions

If you have a data warehouse, push tags through to models so finance and analytics teams can review lift.

Step five: evaluate and iterate

After four to six weeks:

1. Compare test versus control regions
2. Look at total conversions from AI Overview queries across paid and organic
3. Highlight landing pages with strong engagement and expand those
4. Scale or refine based on revenue contribution

This type of system first playbook helps teams learn fast while staying in control of spend and data.

Turning AI Overview ads into a durable advantage

AI Overviews will keep changing, and Google will keep experimenting with monetization. Durable advantage comes from systems that connect GEO, SEO, paid search, and data so you see how AI surfaces affect total demand and adjust with confidence.

Perfect visibility will not exist. Large advertisers will still work with incomplete data. The teams that succeed will build measurement models, experiment often, and align paid and organic decisions.

A sustainable approach includes:

• Entity-driven content and GEO to earn citations
• Campaigns that mirror the natural language of AI Overview queries
• Reporting that blends paid, organic, and AI surfaces
• Clear protections for invalid traffic and policy restrictions

If you already invest in AI SEO and GEO, AI Overview ads are not a separate program. They are another surface where your entities, offers, and proof must align with how users search and decide.

FAQ

Do I need a special campaign type to run ads in AI Overviews?

No. Ads in AI Overviews come from existing search and Performance Max campaigns. New formats such as AI Max are built for AI surfaces, but you can start by aligning current campaigns with AI Overview queries and using broad match with smart bidding.

Can I see AI Overview placements in my Google Ads reports?

Not today. Google does not provide separate placement metrics for AI Overviews. They count under standard search and Top Ads. To understand performance, rely on segments, experiments, and SERP tracking.

Are AI Overview ads available in every country and industry?

No. AI Overview ads are live in selected English-speaking markets. Sensitive YMYL categories, including some finance and healthcare topics, typically do not receive AI Overview ads.

Should small and mid-sized businesses care about AI Overview ads now?

Yes, in proportion to budget. Focus on identifying which queries in your market trigger AI Overviews, then ensure your search and Performance Max campaigns reach those users with clear content and strong tracking.