AI Engines are killing the visibility of traditonal pay per click (PPC) ads.
AI Overviews now appear in 16% of all Google desktop searches in the US, fundamentally changing how users interact with search results.[1]
Click-through rates drop dramatically when AI summaries appear, plummeting from 21.27% to just 9.87%.[2]
User-generated content from platforms like Reddit, YouTube, and Quora dominates AI citations across all major engines.[3]
Brands with higher AI visibility can see significantly better conversion rates despite lower traffic volumes.[4]
More than half (58.5%) of US searches now end without a website visit as users get answers directly from AI summaries.[5]
How AI Search Engines Are Killing Traditional Ad Visibility
The search field is changing more dramatically than at any time since mobile search appeared. AI-powered summaries now appear at the top of search results, changing user behavior and disrupting traditional advertising models.
AI Overviews currently show in 16% of all Google desktop searches in the United States, creating a barrier between users and traditional ads. This isn’t a small layout change – it completely changes how search works. [DigitalBiz] and other studies have analyzed these shifts and their implications for marketers trying to maintain visibility in this new environment.[1]
Click-Through Rate Plummets When AI Overviews Appear
The data shows concerning trends for advertisers using traditional PPC strategies. When AI Overviews appear, click-through rates drop from 21.27% to just 9.87% – a 54% decrease. This happens because users get their questions answered without needing to click any results.[2]
The decline in click-through rates varies by industry, but all sectors show downward trends. When AI Overviews appear:
- Finance queries see CTR drops of up to 62%
- Healthcare searches experience 47% lower CTR
- Retail product queries show 38% fewer clicks
- Service businesses witness 51% CTR declines
These reductions happen because AI Overviews satisfy user intent directly on the search results page. The comprehensive summaries often eliminate the need for users to look at additional resources, including paid advertisements.[6]
Traditional Ad Placements Pushed Below the Fold
Beyond the behavioral changes, there’s a basic visibility problem. AI-generated summaries take up significant screen space, pushing traditional ads further down the page – sometimes completely below the fold, especially on mobile devices.
This positioning challenge creates a double-bind for advertisers:
- Ads receive fewer impressions as they’re pushed out of the viewable area
- Even when visible, they compete with AI summaries that have already answered the user’s query
In many cases, no ads appear alongside AI Overviews at all, particularly for informational and generic queries. This represents a fundamental shift in Google’s approach to monetization and content delivery.[7]
Quality Scores Declining as User Interaction Patterns Change
The ripple effects of AI search extend beyond immediate visibility issues. As fewer users interact with traditional ad placements, Google’s Quality Score metrics are also shifting. Advertisers report gradual declines in Quality Scores even for previously high-performing campaigns.
This occurs because the Quality Score algorithm considers user engagement signals, which naturally decrease as AI Overviews satisfy more queries without requiring clicks. The result is a challenging cycle where lower Quality Scores lead to higher costs per click, further reducing campaign efficiency in an already challenging visibility landscape.[8]
Where AI Engines Source Their Information
Understanding where AI engines get their information is crucial for marketers looking to maintain visibility in this new search landscape. Different AI platforms have distinct preferences for the sources they cite, but certain patterns emerge across the ecosystem.
Top Citation Sources Across Major AI Platforms
AI engines don’t simply use the top 10 search results – they have specific citation preferences that vary by platform. Analysis of millions of AI-generated responses reveals these distinct sourcing patterns:
- ChatGPT primarily uses Wikipedia (47.9% of citations), followed by Reddit (11.3%), Forbes (6.8%), and G2 (6.7%)
- Google AI Overviews prioritizes Reddit (21% of citations), YouTube (18.8%), Quora (14.3%), and LinkedIn (13%)
- Perplexity relies heavily on Reddit (46.7% of citations), with YouTube (13.9%), Gartner (7%), and LinkedIn (5.3%) following
This variance means brands need platform-specific strategies to maximize visibility across the AI search ecosystem. A Wikipedia-focused approach might work well for ChatGPT visibility but would be insufficient for Google AI Overviews or Perplexity.[9]
The Power of User-Generated Content in AI Responses
User-generated content platforms like Reddit, YouTube, Quora, and LinkedIn dominate across all major AI engines. These platforms consistently rank higher than traditional media sources and even brand websites in many cases.
This preference for user-generated content stems from several factors:
- AI engines value conversational, natural language that mimics human communication
- Community-vetted information (upvotes, comments, engagement) serves as a quality signal
- Question-and-answer formats on these platforms align with how users interact with AI tools
- These platforms often contain real-world experiences and practical applications
For marketers, maintaining an authentic presence on these platforms is now essential for AI visibility. Brands must participate genuinely in relevant communities, share expertise without overtly promoting products, and build credibility through consistent value-added contributions.[10]
Query Fan-Out: How Google AI Mode Works
Google’s AI Mode uses a new approach to search through its query fan-out technology. Unlike traditional search that processes a single query, AI Mode expands a user’s question into dozens of related subtopics and searches for them simultaneously.
When a user asks “What’s the best project management software for small teams?” Google AI doesn’t search for that exact phrase. Instead, the system breaks the question into multiple components and searches across different data sources:
- Project management software features
- Small team collaboration tools
- Pricing comparisons for project management solutions
- User reviews and satisfaction metrics
- Industry-specific project management needs
- Free vs. paid project management options
This fan-out technology means brands must optimize for a much broader set of related queries and ensure their content thoroughly addresses various aspects of a topic. Shallow content that targets only primary keywords will be less likely to appear in AI-generated responses that pull from multiple related searches.
Industry-Specific Impact and Performance Data
The impact of AI search varies significantly across industries, with some sectors seeing more dramatic shifts than others. Understanding these industry-specific patterns can help marketers develop more targeted strategies.
Banking and Finance: 32.2% Market Dominance by Leaders
In the banking and financial services sector, established brands are using AI visibility to further strengthen their market positions. Bank of America leads banking mentions with an impressive 32.2% visibility across AI platforms, followed by competitors like SoFi (25.7%) and LightStream (20.2%).[11]
This concentration of visibility among industry leaders creates significant challenges for smaller financial institutions and fintech startups. Without strategic intervention, AI search could further consolidate market share among dominant players.
However, the data also reveals opportunities for specialized financial service providers. Niche players with clear value propositions in specific domains (retirement planning, first-time homebuyer programs, student loan refinancing) can achieve disproportionate visibility when users ask questions in these specialized areas.
Healthcare, Retail, and Software Category Leaders
The pattern of category leaders dominating AI search visibility extends across other major industries:
- Healthcare: Mayo Clinic dominates with 14.1% visibility across AI platforms, with Cleveland Clinic and Johns Hopkins Hospital following[12]
- Retail: Amazon maintains 57.3% visibility with Walmart capturing 45.9%, creating a duopoly in general retail mentions[13]
- Software: Category-specific leaders like QuickBooks (accounting), Salesforce (CRM), and HubSpot (marketing) consistently appear in top positions for their respective domains
AI engines often mention multiple competing products within responses, creating a more level playing field than traditional search where only one company can rank in position #1. This means brands can achieve meaningful visibility without necessarily being the market leader, provided they excel in specific use cases or customer segments.
Higher Conversion Rates Despite Lower Traffic Volume
While AI search is driving less overall traffic to websites, the quality of that traffic is often superior. Research shows that visitors who arrive from AI-powered search convert at significantly higher rates than traditional organic traffic:
- An insurance company saw LLM visitors convert at 3.76% compared to 1.19% for organic search traffic
- An e-commerce retailer experienced a 5.53% conversion rate from LLM traffic versus 3.7% from organic search
This conversion advantage occurs because users conduct extensive research within the AI interface before clicking through to a specific site. When they do click, they’re further along in the decision-making process and more likely to convert.[4][14]
The implications are significant: while overall traffic may decrease, the value per visitor can increase substantially. Marketers need to shift their focus from raw traffic metrics to conversion quality and adjust their attribution models to properly value these high-intent AI-sourced visitors.
Adapting Your PPC Strategy for the AI-First Search Era
1. Build Technical Foundations for Maximum AI Visibility
The technical underpinnings of your website significantly impact how AI engines discover, interpret, and cite your content. Implementing these foundational elements is essential:
- Implement semantic HTML5 markup: Use proper header tags (H1, H2, H3) and structured elements (nav, main, article, section) to help AI crawlers understand your content’s organization
- Add comprehensive schema markup: Include JSON-LD schema for products, FAQs, how-to content, events, and organization information
- Ensure server-side rendering: AI crawlers often have limited time budgets and may abandon JavaScript-heavy pages
- Optimize for mobile-first indexing: AI engines prioritize mobile-friendly content that loads quickly and displays properly on all devices
- Create XML sitemaps with freshness signals: Include lastmod date attributes to signal content currency
These technical optimizations ensure AI engines can effectively crawl, process, and understand your content, increasing the likelihood of citation in AI-generated responses.[15]
2. Optimize Content for AI Engine Citations
Content strategy must work for both human readers and AI systems. The most effective content for AI visibility follows these principles:
- Front-load key information in the first 160 characters: Research shows AI engines heavily weight the opening sentences of content blocks
- Structure content as direct answers to specific questions: Use clear question-based headings followed by concise, authoritative responses
- Incorporate relevant entities and semantic relationships: Explicitly mention related concepts, categories, and specific entities
- Create comprehensive topic coverage: Address all aspects of a subject rather than narrowly focusing on primary keywords
- Use clear, factual statements with specific data points: AI engines favor precise information over vague generalizations
This content approach aligns with how AI engines extract and synthesize information, increasing your chances of being cited as an authoritative source.[15]
3. Develop Cross-Channel Authority Beyond Your Website
AI engines don’t limit their information gathering to your website – they pull from across the entire digital ecosystem. Building authority across multiple platforms is now essential:
- Build an authentic presence on Reddit, Quora, and YouTube: Engage genuinely in communities related to your industry
- Create educational video content with optimized transcripts: YouTube is a major citation source for Google AI Overviews
- Develop thought leadership content for LinkedIn: Professional insights are frequently cited by AI engines
- Earn mentions in authoritative publications: Digital PR efforts should target publications AI engines frequently cite
- Build Wikipedia presence when appropriate: For established brands, Wikipedia remains a crucial citation source
This distributed approach to authority building ensures your brand appears in multiple information sources that AI engines trust and reference. Local SEO also becomes critical – even for national brands – as Google’s AI features often prioritize location-based results regardless of query specificity.[3]
4. Implement Measurement Systems for AI Visibility
Traditional SEO metrics don’t fully capture performance in the AI search era. New measurement approaches are needed:
- Track brand mentions across AI platforms: Monitor how frequently your brand appears in AI-generated responses
- Analyze share of voice within your category: Measure how often you’re mentioned compared to competitors
- Monitor LLM-generated traffic in analytics: Implement tracking for visitors coming from AI platforms
- Evaluate conversion rates for AI-sourced traffic: Compare performance against traditional search traffic
- Document specific queries where your brand appears: Identify patterns in the types of questions that trigger your brand mentions
These measurement systems provide insights into your AI search performance and help identify optimization opportunities that might be missed by focusing solely on traditional metrics.[15]
Act Now or Risk Becoming Invisible in the AI-Dominated Landscape
The window for establishing AI search dominance is closing rapidly. Early movers are already securing their positions as the trusted authorities that AI engines consistently cite. As these citation patterns become established, they create a virtuous cycle that reinforces the visibility of already-dominant brands.
The risks of inaction are substantial:
- Diminishing visibility in traditional search: As more queries trigger AI responses, traditional search traffic continues to decline
- Increased cost for paid visibility: Competition intensifies for fewer available ad positions
- Market share erosion: Competitors who optimize for AI search capture mindshare and customer relationships
- Reputation management challenges: Without proactive AI optimization, your brand narrative is controlled by others
The brands that succeed in this new environment will be those that adapt quickly and implement comprehensive strategies across technical foundations, content optimization, and cross-channel authority building.
The future of search isn’t just coming – it’s already here. With 16% of desktop searches now showing AI Overviews and 58.5% of searches ending without a website visit, the transformation is well underway. The question isn’t whether AI will change your market, but whether your brand will be visible when it does.[1][5]
For marketers ready to adapt, these changes present tremendous opportunities to establish authority, connect with high-intent visitors, and drive superior conversion rates. The brands that invest in AI search optimization today will be the market leaders of tomorrow.
DigitalBiz provides comprehensive solutions to help forward-thinking marketers navigate the AI search revolution with data-driven strategies for maximum visibility in this rapidly evolving landscape.
References
1 Semrush Report on AI Overviews’ Impact on Search in 2025. Available at: Semrush Blog
2 CampaignLive, 2025. 1% click-through rate: How Google AI Overviews is killing publishers. Available at: CampaignLive Article
3 Search Engine Land analysis of AI citation sourcing in 2025. Available at: Search Engine Land
4 Ahrefs, 2025. Ahrefs study finds AI search visitors convert 23x higher than organic traffic. Available at: PPC Land Article
5 Digital Rebel Marketing, 2025. AI Search’s Impact on PPC Advertising. Available at: Digital Rebel Marketing Blog
6 Press Gazette, 2025. Publishers ‘lose 50% of clickthrough rate due to AI Overviews’. Available at: Press Gazette
7 Pew Research Center, 2025. Google users are less likely to click on links when an AI summary appears. Available at: Pew Research Center Report
8 IBM, 2025. AI in Banking: How financial institutions adopt AI. Available at: IBM AI in Banking
9 Search Engine Land, 2025. How to get cited by AI: SEO insights from 8000 AI citations. Available at: Search Engine Land Article
10 Favoured, 2025. UGC Trends in 2025: Key Insights on User-Generated Content. Available at: Favoured UGC Report
11 SEO Clarity, 2025. Impact of Google’s AI Overviews: SEO Research Study. Available at: seoClarity Research
12 Intuition Labs, 2025. Top 20 Medtech Companies Leveraging AI in 2025. Available at: Intuition Labs Report
13 MobiDev, 2025. AI in Retail: Use Cases, Challenges and Best Practices. Available at: MobiDev AI in Retail Guide
14 Forbes, 2025. Study Shows LLM Conversion Rate Is 9x Better — AEO Is Coming. Available at: Forbes Article
15 Progress Software, 2025. Search in 2025 – Rise of AI, User-Generated Content & Future of SEO. Available at: Progress Software Blog