Data Collected

We analyzed healthcare keywords at the same point each December across three years to understand:

• Year-over-year changes in AI Overview deployment rates
• Query type patterns (clinical vs. local vs. sensitive topics)
• Specialty-level expansion patterns within healthcare
• Stability and volatility trends over time

Key Finding

Google expanded AI Overview coverage in healthcare from 59% to 89% over two years — but drew clear boundaries. Clinical content is now near-saturated (93-100% coverage), while local "near me" queries saw a complete reversal: from 100% AI Overview presence in 2023 to 0% today. Google isn't treating all healthcare queries the same. They're matching AI presence to query type — and they've stabilized their approach.

The Three-Year Transformation

December 2023: 59% of Keywords Had AI Overviews

In late 2023, Google was still in expansion mode with AI Overviews (then called SGE). Healthcare showed moderate coverage, with roughly six in ten queries triggering an AI-generated response.

This was the testing phase. Google was learning where AI helped users and where it created problems — particularly in a Your Money Your Life (YMYL) category like healthcare.

December 2024: 84% of Keywords Had AI Overviews

The biggest expansion happened between 2023 and 2024. AI Overview presence jumped 25 percentage points in a single year as Google rolled out the feature broadly following Google I/O 2024.

Healthcare saw aggressive growth across most clinical categories during this period.

December 2025: 89% of Keywords Have AI Overviews

Growth continued but decelerated significantly — just 5 percentage points year-over-year. This suggests Google has reached near-saturation for the query types it intends to cover.

The slower growth isn't hesitation. It's refinement. Google drew lines on where AI belongs in healthcare search.

The Intent Interpretation

The 30 percentage point expansion from 2023 to 2025 wasn't uniform. It reflects Google's learning about healthcare search intent:

• Clinical information intent → Heavy AI treatment (symptoms, treatments, conditions)
• Local provider intent → AI removed entirely (Google reversed course)
• Sensitive health topics → AI consistently excluded (crisis, mental health)

Google is matching SERP treatment to query risk profile, not just search volume or category.

Where Google Went All-In: Clinical Content

Query Type Breakdown (December 2025)
Treatment and procedure queries now show 100% AI Overview presence — up from 45% in 2023. This represents a 55 percentage point increase.

Pain-related queries show 98% AI Overview presence — up from 58% in 2023. This represents a 40 percentage point increase.

Symptoms and conditions queries show 93% AI Overview presence — up from 57% in 2023. This represents a 36 percentage point increase.

Medical coding queries (ICD-10, CPT) show 90% AI Overview presence — up from 67% in 2023. This represents a 23 percentage point increase.

What This Means for Clinical Content
If you're measuring organic traffic on treatment pages, symptom guides, or condition explainers — and seeing declines while rankings hold steady — AI Overviews are likely the cause.

A Position 1 ranking on "rotator cuff surgery recovery" doesn't deliver the same traffic it did in 2023. The AI Overview answers the query before users reach organic results.

The Specialty Breakdown

• Google's expansion varied significantly by medical specialty. Core clinical specialties saw the highest coverage:
• Genetic/Genomic content: 97% have AI Overviews (up from 63% in 2023)
• Cardiology content: 96% have AI Overviews (up from 63% in 2023)
• Urology content: 96% have AI Overviews (up from 68% in 2023)
• Gastroenterology content: 94% have AI Overviews (up from 41% in 2023)
• Orthopedics content: 94% have AI Overviews (up from 63% in 2023)
• Neurology content: 89% have AI Overviews (up from 64% in 2023)
• Lower coverage categories include:
• Primary Care content: 74% have AI Overviews (up from 66% in 2023)
• Mental Health/Behavioral content: 63% have AI Overviews (up from 58% in 2023)
• Eating Disorders content: 63% have AI Overviews (up from 32% in 2023)
• The pattern: clinical specialties with clear diagnostic and treatment pathways saw the most aggressive expansion. Categories intersecting with sensitive topics or local intent saw more conservative treatment.

Where Google Pulled Back: The Reversal Story

Local "Near Me" Queries: 100% → 0%

This is the most significant finding in the data. Google completely reversed its approach to local healthcare searches.

• December 2023: 100% of local/provider intent queries had AI Overviews
• December 2024: 14% of local/provider intent queries had AI Overviews
• December 2025: 0% of local/provider intent queries have AI Overviews

Queries affected include searches like "dermatologist near me," "cardiologist near me," "pediatric dentist near me," and "best family doctor near me."

Google tested AI Overviews on these queries. Then removed them entirely.

Why This Matters

User-Generated Content
For healthcare practices, clinics, and hospital systems: your local SEO investment still pays off. Google has decided — at least for now — that local healthcare provider searches should be handled by traditional local results (Maps, local pack, organic listings) rather than AI summaries.

The queries that drive new patient acquisition remain traditional SEO territory.

Visual and Imaging Content: 45% → 30%

Queries seeking medical images, X-rays, or diagnostic visuals also saw Google pull back:

• December 2023: 45% had AI Overviews
• December 2025: 30% have AI Overviews

Queries like "broken ankle x-ray," "MRI results interpretation," and "skin cancer pictures" don't lend themselves to text-based AI summaries. Google recognized this and reduced coverage.

This creates an opportunity: image-rich medical content faces less AI competition than text-based clinical content.

Where Google Consistently Excludes AI

Some healthcare topics have shown zero or near-zero AI Overview presence across all three years. Google has clearly made policy decisions to keep AI out of these areas:

Consistently Excluded (0% AI Overviews)

• Self-harm and suicide-related queries
• Specific eating disorder names (anorexia, bulimia)
• Crisis intervention terminology
• Addiction-related queries

Consistently Low Coverage

• Mental health crisis terminology
• Abuse-related queries
• Visual diagnostic content

The Implication

If your content focuses on sensitive mental health topics, traditional SEO fundamentals still apply. Rankings matter. Featured snippets matter. AI isn't intercepting these users — Google has determined that human-curated results are more appropriate.

The Stability Factor: Volatility Is Over

Early 2024: High Volatility

If your content focuses on sensitive mental health topics, traditional SEO fundamentals still apply. Rankings matter. Featured snippets matter. AI isn't intercepting these users — Google has determined that human-curated results are more appropriate.

Late 2025: Stable Deployment

By late 2025, monthly volatility dropped to approximately 5 percentage points. Google has settled into a steady state.

What This Means for Planning

The wild experimentation phase is over. What you see now is Google's established approach to healthcare AI Overviews. You can plan content strategy around these patterns with reasonable confidence they'll persist.

Search Volume Analysis

AI Overview deployment in healthcare does not significantly vary by search volume:

• High volume keywords (100K+ monthly searches): 89% have AI Overviews
• Medium volume keywords (10K-100K monthly searches): 88% have AI Overviews
• Low volume keywords (1K-10K monthly searches): 89% have AI Overviews
• Very low volume keywords (under 1K monthly searches): 100% have AI Overviews

Google isn't reserving AI Overviews for high-traffic queries. Even long-tail, low-volume medical queries now predominantly feature AI-generated responses.

The decision factor isn't volume — it's query type and intent.

Technical Methodology

Data Source: BrightEdge Generative Parser™

Analysis Approach:

• Healthcare keywords analyzed at equivalent points in December 2023, December 2024, and December 2025
• AI Overview presence tracked by specialty area (L2 taxonomy) and query type
• Query intent patterns categorized by clinical, local, sensitive, and visual content types
• Stability measured by monthly variance in AI Overview deployment rates

Measurement Periods:

• December 2023 snapshot: December 22, 2023
• December 2024 snapshot: December 22, 2024
• December 2025 snapshot: December 22, 2025
• Trendline data: Daily tracking November 2023 through December 2025

All figures expressed as percentages to protect proprietary dataset composition.

Key Takeaways

• The Coverage Expansion: Healthcare AI Overview presence grew from 59% to 89% over two years — a 30 percentage point increase. Most growth occurred between 2023 and 2024.
• The Clinical Saturation: Treatment queries (100%), pain-related queries (98%), and symptom queries (93%) are now near-fully covered by AI Overviews. Clinical content is AI territory.
• The Local Reversal: "Near me" and provider-finding queries went from 100% AI Overview coverage in 2023 to 0% in 2025. Google completely reversed course on local healthcare search.
• The Sensitivity Boundaries: Self-harm, eating disorder names, crisis terms, and addiction queries remain consistently excluded from AI Overviews across all three years.
• The Specialty Pattern: Clinical specialties (Cardiology, Gastro, Ortho) show 94-97% coverage. Mental health and primary care show 63-74% coverage.
• The Stability Shift: Monthly volatility dropped from ~20 percentage points in early 2024 to ~5 percentage points in late 2025. Google's approach has stabilized.

Using BrightEdge AI Catalyst, we analyzed eCommerce prompts across Google AI Overviews and ChatGPT throughout the holiday shopping season. We've already shared WHO each platform cites — now we're examining HOW CONCENTRATED those citations are. The patterns reveal very different distribution curves that marketers should understand when measuring AI visibility.

Data Collected

We analyzed citation sources across both AI platforms to understand:

• Which domains each AI returns to repeatedly across many queries

• How concentrated citations are among top sources

• How often the same URL gets reused across different prompts

• Whether the same content surfaces differently on each platform

Key Finding

AI Overviews concentrates citations among a smaller set of trusted sources — its top 10 domains capture 39% of all shopping citations. ChatGPT distributes citations across a much wider pool — its top 10 domains capture just 22%. One retailer homepage appears in roughly 1 of every 4 AI Overview shopping responses. The same optimization wins on both platforms, but understanding the distribution curves helps you measure success accurately.

The Concentration Gap

AI Overviews: Deep Trust in Fewer Sources

AI Overviews returns to the same sources repeatedly. The top 10 domains capture 39% of all eCommerce citations, and a single retailer homepage appears in approximately 26% of all shopping queries.

This concentration pattern means that when AI Overviews trusts a source, it cites that source across many different queries. Winning visibility on AI Overviews means joining a concentrated set of repeatedly-cited sources.

The Strategic Interpretation

This isn't about one platform being better than the other. It reflects different approaches to sourcing information for shoppers.

AI Overviews builds on established, trusted sources — going deep with content it returns to across many related queries.

ChatGPT casts a wider net — pulling from a broader universe of sources and going wide to find query-specific content.

URL Reuse Patterns: The Starkest Contrast

How Often Does the Same URL Get Cited?

The URL reuse data reveals just how different these platforms behave.

AI Overviews' most-reused single URL appears in approximately 26% of all shopping queries. When AI Overviews finds a source it trusts for a category, it returns to that source repeatedly.

ChatGPT's most-reused single URL appears in approximately 1% of queries. Even ChatGPT's "favorite" sources are only cited in a small fraction of responses.

What This Looks Like in Practice

For AI Overviews, a Consumer Reports buying guide might get cited in 27 different shopping queries — from coffee makers to mattresses to microwaves. The same trusted source serves many different user needs.

For ChatGPT, a detailed RTINGS TV review might get cited in 48 queries — but those are almost all TV-specific queries. ChatGPT finds the deep expert source for each specific topic rather than reusing general buying guides across categories.

Same Content, Different Visibility Curves

The Measurement Implication

Your content can win on both platforms — but where and how often it appears will differ.

On AI Overviews, a winning piece of content may surface repeatedly across many related queries. If you're cited, you may be cited often.

On ChatGPT, a winning piece of content may surface for specific queries where it's the best match. You may be cited less frequently, but with more precision.

This isn't a strategy problem — it's a measurement reality. Tracking visibility on both platforms gives you the complete picture of how your content performs in AI search.

Platform Favorites: Different Sources for Different Platforms

Each Platform Has Go-To Sources

When we looked at specific URLs, clear patterns emerged. Each platform has sources it returns to repeatedly — and they're often different sources.

One TV review site's "best TVs" page was cited in 48 queries by ChatGPT but 0 by AI Overviews.

One trusted buying guide index page was cited in 27 queries by AI Overviews but 0 by ChatGPT.

Both are high-quality sources. Both provide genuine value to shoppers. But each platform has developed its own preferences for which sources to trust and return to.

The "Optimize Once" Reality

This doesn't mean you need different content strategies for each platform. Quality content that serves user needs can surface on both. The difference is in how each platform distributes that visibility.

AI Overviews may cite you frequently across many queries once you're in its trusted set.

ChatGPT may cite you precisely for the specific queries where you're the best source.

Both are wins. Understanding the pattern helps you interpret your visibility data correctly.

What This Means for Brands

Track Both Scoreboards

The concentration difference means raw citation counts will look different across platforms — and that's expected.

A source cited 20 times by AI Overviews and 5 times by ChatGPT isn't necessarily "losing" on ChatGPT. It may simply reflect the different distribution curves. ChatGPT's 5 citations might represent 5 highly specific queries where your content was the best match.

Conversely, being cited 0 times by AI Overviews but 15 times by ChatGPT doesn't mean AI Overviews is ignoring you — your content may simply serve queries that ChatGPT handles differently than AI Overviews.

Understand Your Category

The concentration patterns may vary by category. Buying guides and category-level content may see more reuse on AI Overviews. Deep product-specific reviews may see more precise matching on ChatGPT.

This aligns with what we found earlier: AI Overviews leans on editorial and UGC content (YouTube, Reddit, review sites) while ChatGPT leans on retailer and product sources. The concentration data adds another layer — AI Overviews not only favors different source types, it returns to those sources more repeatedly.

One Strategy, Two Visibility Patterns

The actionable insight isn't "build two strategies." It's "measure two outcomes."

Same content optimization. Same focus on quality, relevance, and user value. But when you check your AI visibility metrics, expect to see different patterns:

AI Overviews: Fewer total queries, but higher citation frequency per query when you do appear.

ChatGPT: More total queries in your addressable universe, but lower citation frequency as visibility spreads across more sources.

Both patterns represent success. Understanding them helps you set appropriate benchmarks and interpret your data correctly.

Technical Methodology

Data Source: BrightEdge AI Catalyst

Analysis Approach:

• eCommerce prompts analyzed across Google AI Overviews and ChatGPT

• Citation sources extracted and categorized by domain and URL

• Domain concentration calculated (share of citations held by top domains)

• URL reuse patterns measured (how many prompts cite the same URL)

• Cross-platform comparison for shared vs. platform-exclusive sources

Key Metrics:

• Top 10 domain concentration (% of total citations)

• Single URL maximum reuse (% of queries citing one URL)

• URL uniqueness rate (% of URLs cited only once)

• Domain overlap analysis across platforms

Measurement Period: Holiday Shopping Season 2025

Key Takeaways

The Concentration Gap: AI Overviews' top 10 domains capture 39% of citations. ChatGPT's top 10 capture just 22%. AI Overviews goes deep with trusted sources. ChatGPT goes wide across more.

The Reuse Pattern: AI Overviews' most-cited single URL appears in ~26% of shopping queries. ChatGPT's most-cited URL appears in ~1%. AI Overviews returns to favorites. ChatGPT pulls fresh sources.

The Uniqueness Rate: 61% of URLs cited by ChatGPT appear in only one query. ChatGPT finds specific sources for specific queries rather than reusing general pages.

The Platform Favorites: Each platform has sources it trusts and returns to repeatedly — and they're often different sources. The same quality content can win on both, but visibility patterns will differ.

The Measurement Reality: Same optimization strategy works for both platforms. But understanding the different distribution curves helps you interpret visibility data and set appropriate benchmarks.