Google’s AI Overviews now appear across search results with varying frequency. However, in certain categories, they dominate entirely. According to Adthena:

• Finance queries see AI Overviews on 79% of longer searches with five or more words. 
• Retail shows 84% visibility for comparison and product discovery queries in the 9-10 word range. 
• Healthcare also triggers high AI Overview penetration even when users are searching short medical questions of 1-3 words.

You know organic traffic faces headwinds. What you might underestimate is how severe the downstream impact on paid search can be. Here’s what that looks like in practice.

AI Overviews’ impact on paid search

AI Overviews are systematically changing paid search, affecting everything from click volume to auction dynamics and conversion behavior. They are accelerating structural trends that are already reshaping search, including SERP saturation, automated bidding, Performance Max adoption, and broad match expansion. 

What makes AI Overviews significant is the speed of the rollout. In many verticals, Google had compressed what would have normally been a multi-year transition into mere months. Understanding the impact on your own paid search efforts requires examining how AI answers have reshaped each component of your campaign performance.

AI Overviews drive lower response rates

So, how much have response rates been impacted by AI Overviews? Recent data from Seer Interactive reveals the scale of the decline. Paid CTR on queries featuring AI Overviews plummeted by 68%, dropping from 19.7% to 6.34% between June 2024 and September 2025.

At the same time, we saw organic CTR fall 61% on the same queries, but the steeper paid decline suggests AI Overviews reshape where paid ads appear and who clicks them, not simply their overall presence.

The trend accelerated sharply in July 2025 when paid CTR collapsed from approximately 11% to 3% in a single month. One month. This happened as Google expanded AI Overviews more aggressively into commercial and navigational queries, demonstrating AI Overviews’ direct impact on paid search response rates.

What we’re finding is that these declines are the most severe for non-branded informational queries. But it’s not all bad news. Branded search and high-intent transactional queries are showing greater resilience, with many advertisers seeing minimal impact on their core conversion-driving terms.

AI Overviews contribute to higher CPCs through inventory compression

We’re also finding a direct correlation between AI Overviews and the cost of paid search campaigns. That’s because the response rate decline is directly driving cost-per-click (CPC) inflation through supply and demand mechanics.

Google Search spending grew 9% year-over-year in Q1 2025, but click growth was only 4%. That 5% gap represents more dollars chasing fewer clicks across many industries. 

AI Overviews amplify this CPC inflation through several mechanisms. Some of that has to do with ad positioning. Research on ad positioning shows that ads that appear above an AI Overview still perform reasonably well. But the ads below are seeing a dramatic reduction in impression share and CTR. 

At the same time, double-serving policies are concentrating impression share among larger advertisers, which is forcing smaller ones to bid more aggressively. Automated bidding systems optimize toward conversion predictions rather than cost efficiency, which means campaigns are paying premium CPCs as the click inventory shrinks.

AI Overviews collapse the consideration phase

We’re also seeing a dip in the consideration phase of the buyer’s journey. Customer journeys that used to take up to a few days, AI Overviews can now compress into minutes by handling the research and comparison activities that traditionally occurred across multiple search sessions.

For example, think back to how in, say, 2023 a search for [best project management software for remote teams] would have triggered a multi-day sequence for users who would first, perhaps, click through to organic results, then read some comparison articles, then perhaps visit some vendor websites, and, finally, after maybe 7-14 days, they might finally convert. 

Today, when you search for [best project management software for remote teams], you could convert in a single session. An AI Overview can give users everything they need at once: a comparison table with features, pricing, and use cases, then refined recommendations for two or three options. People could decide in hours instead of weeks.

This compression reshapes campaign performance in three ways: 

• Smaller retargeting pools: Retargeting pools shrink dramatically because fewer clicks during research means there are fewer users entering remarketing audiences. While Google has lowered audience minimums from 1,000 to 100 users, the shift is meant to help boost small business campaigns, but it still means that a campaign that historically would have built up a 10,000-user pool from informational traffic might now capture only 3,000 users.
• Less brand awareness: Brand awareness suffers when users never visit your site during research, entering the purchase decision having consumed AI-generated comparisons rather than experiencing your messaging directly.
• AI Overviews mentions are a must: AI citation creates a winner-take-all dynamic. Being mentioned in AI Overviews becomes a primary determinant of visibility. Brands that appear in the AI answer capture disproportionate traffic, while those excluded lose ground entirely.

AI Overviews create a quality-over-quantity trade-off

The journey compression caused by AI Overviews is producing a counterintuitive economic outcome. As click volume declines, conversion rates improve.

A benchmark analysis of 16,446 campaigns confirms the pattern. While overall click volume declined across nearly all query types in 2025, 65% of industries actually saw improved conversion rates.

For many of those industries, the jump was substantial. For example, education and instruction saw conversion rates jump 43.87% year-over-year, while sports and recreation climbed 42.43%. 

So why is this happening?

The improved conversion rates are reflective of AI Overviews pre-qualifying users by answering their basic questions before they click ads. This filters out a lot of the users who are simply seeking general information without any intention to convert and leaving only high-intent prospects.

These improved conversion rates could also potentially partially offset CPC inflation in many scenarios. For example, let’s say a business software campaign is generating 1,000 clicks at $2.00 CPC. The campaign generated a 5% conversion rate, resulting in 50 conversions at a $40 CPA. 

Then, let’s say, Google rolled out AI Overviews for their keywords, and it compressed the customer journey. The same campaign might then generate fewer clicks, say 700, at $2.90 CPC and a higher 7% conversion rate, producing 49 conversions at $41.43 CPA. The effective cost increase is only 3.6% despite 45% CPC inflation and 30% volume decline.

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4 strategic pivots for the AI search era

Paid search still offers opportunities for advertisers who adapt quickly. Let’s look at four strategies you can incorporate into your own campaigns that align with the new realities of AI-mediated search.

1. Monitor informational intent performance and optimize accordingly

Since AI Overviews are fundamentally changing the economics of informational queries, they require extra scrutiny from you. Implement systematic monitoring rather than blanket exclusions of informational keywords to identify which keywords still deliver value and which have become budget drains.

Begin by understanding which informational keywords still hold value. Informational keywords like “what is,” “how to,” and “guide to” are being cannibalized by AI Overviews at substantial rates. In finance, AI Overviews appear on 79% of longer queries, while in retail they show up on 84% of comparison searches.

However, transactional keywords like “buy,” “best,” “compare,” and “near me” maintain higher CTRs because AI typically doesn’t complete transactions. The user needs to click away from AI Overviews to complete their transaction.

We’re still seeing 69% of transactional searches in AI Mode result in clicks to websites. Branded search remains largely intact, with AI Overviews primarily affecting non-branded informational queries.

To identify which informational keywords still perform, follow these steps:

• Start by pulling 90 days of Google Ads query data. 
• Next, you’ll want to flag queries that contain informational trigger words. 
• Then, cross-reference that data with Google Search Console, since GSC now tags these in performance reports, to identify which queries trigger AI Overviews. 
• Finally, you can calculate CTR and conversion rate for informational versus transactional queries to establish your baselines.

For the informational queries that show less than 1% CTR and less than 50% of your average conversion rate, you have three options: 

• Test whether you can improve performance by focusing on creative optimization for unique offers rather than information. 
• Reduce your bids on those queries to maintain presence at a lower cost while continuing to monitor for changes.
• Shift your budget toward transactional and navigational keywords that are performing better, while maintaining minimal informational presence to bolster brand visibility.

Note: An important exception applies for brands that are consistently being cited in AI Overviews. Since cited brands are seeing a 91% paid CTR lift, this suggests that these informational keywords could become strategic assets. 

If your brand appears in AI Overviews for informational queries like “best accounting software for freelancers,” it may warrant maintaining or increasing bids on those terms. You’ll also want to scrutinize for any uncited queries more aggressively to see if you’re missing any opportunities.

2. Prioritize feed quality

Yes, generative AI can summarize and compare, but it can’t invent price, inventory, or availability from thin air. This creates a structural advantage if you have robust product feeds in Google Shopping, Hotel Ads, and local inventory.

Google’s AI Mode shopping experience, powered by the Shopping Graph with 50 billion product listings refreshed hourly, relies entirely on structured product data from Merchant Center feeds. When users search, for example, for “breathable bamboo crib sheets under $40,” the AI can only surface products whose feeds include that level of attribute specificity. 

Shopping ads now appear directly within AI Overviews for queries with commercial intent, powered by existing Shopping and Performance Max campaigns.

Feed optimization requires four priorities: 

• Attribute enrichment must include contextual details like “waterproof for rainy commutes” or “red couch for small apartment” that match natural language queries. 
• Real-time accuracy matters as Google updates listings hourly and outdated data filters products out of AI Mode entirely. 
• Structured data completeness determines visibility. Google’s AI prioritizes products with rich, complete attribute data over listings with minimal information. 
• Rich media assets have become table stakes. Google’s AI prioritizes listings with five or more product images and video content, with virtual try-on features integrated across Search, Shopping, and Images, driving visual discovery.

3. Craft creative that differentiates

Since users have already learned about the features and benefits they were querying in AI Overviews before clicking, your ad must answer why they should choose you and why they should choose you now.

Lead with unique value propositions instead of generic benefits. For example:

• “Project Management Software for Teams” is generic and would convert less often than a specific offering like “14-Day Free Trial + Free Migration from Asana/Monday.”
• An overly-general value prop like “Tax Preparation Services” would be expected to underperform something much more specific and unique like “Same-Day CPA Review | $50 Off Filing This Week.”

You’ll also want to leverage ad extensions aggressively. Research shows that ads can appear above or below AI Overviews depending on query type and industry. When AI Overviews pushes everything down the page, extensions are your way to stay visible. 

Ads that use all available sitelinks, callouts, and structured snippets can occupy 2-3 times the SERP real estate of basic ads. Taking up that extra space is critical as ads now appear within AI Overviews themselves for commercial intent queries.

You can use responsive search ads to test value proposition hypotheses at scale. Start by loading Responsive Search Ads (RSAs) with diverse headlines that test:

• Urgency (i.e., “Limited Availability”).
• Risk reversal (i.e., “No Credit Card Required”).
• Social proof (i.e., “4.9 Stars, 5,000+ Reviews”).
• Differentiation (i.e., “Only Platform with Native Zapier Integration”). 

Then let Google’s machine learning identify which messages resonate with high-intent users who’ve already completed their research.

If your brand is cited in AI Overviews for specific use cases, reference those directly. For example, if AI Overview consistently recommends your accounting software for “freelancers,” you’ll want to include “Built for Freelancers” in headlines to align with the recommendation users just consumed.

4. Embrace audience data

These days, it’s all about the data. As keyword-based targeting becomes less reliable in an AI-dominated search environment, first-party audience data is becoming more and more your sustainable competitive advantage. When AI answers queries without regard to keyword precision, your existing customer relationships represent what AI can’t disintermediate.

What we mean is that you know your audience already. Take advantage of that.

Customer Match lists allow you to upload email lists, phone numbers, and CRM data, with Google lowering the minimum from 1,000 to 100 users in 2025. Remember, users who’ve already engaged with your brand will convert at significantly higher rates than cold traffic and search with intent to re-engage rather than research.

It’s also important to build granular website visitor segments based on the behaviors that signal purchase intent. You want to represent all prospects who have moved beyond research: 

• Product page viewers who didn’t convert.
• Abandoned cart users.
• Visitors to pricing and comparison tools.
• Users with 10+ minute sessions.

Target these audiences with messaging that assumes they’ve already completed their evaluation through AI-powered search.

Use similar audiences and lookalikes to help Google’s AI identify users who match your highest-value customer profiles. Performance Max and Demand Gen campaigns work best when fed customer lists and purchase history, which allows for identifying intent patterns beyond keywords.

In the AI Overview environment, shift your budget from old-school, keyword-heavy Search campaigns to audience-driven Performance Max and Demand Gen formats that prioritize first-party data. Build email capture mechanisms through gated content and progressive profiling. Then, integrate your CRM with Google Ads to activate customer data for targeting and bidding. 

A good place to start is by reallocating an underperforming informational query budget to audience-based campaigns, and then scaling based on results.

First-party data provides higher signal quality than behavioral targeting alone, which gives advertisers with robust data infrastructure measurable advantages in conversion rates and customer acquisition costs.

Adaptation is the key to today’s search success

AI Overviews are changing paid search. There’s no doubt about it. And the data shows the real pressure paid search is facing.

But there’s good news: you can still succeed if you adapt your strategy to match how search works now — not how it worked two years ago.

• Start by monitoring which of your informational queries are still working, rather than excluding them all.
• Then, prioritize feed quality for Shopping campaigns.
• Make sure you write ads that differentiate rather than inform.
• And definitely build first-party audience lists before your competitors do.