Google AI Overviews tends to surface pulmonology practices for immediate, local, symptom-driven searches ("pulmonologist near me for chronic cough"), pulling from Google Business Profiles, reviews, and indexed web pages. ChatGPT tends to influence patients earlier, during research-phase questions like "what does a pulmonologist do for sleep apnea," drawing on training data, web content, and cited sources when browsing is active. A practice that wants referrals from both needs to be visible in local map-pack style data and in the broader web content that language models read and summarize.
How each engine gathers and presents local clinic options
Google AI Overviews builds its answer from the same signals that power traditional Google Maps and local search results: your Google Business Profile, star ratings, review text, proximity to the searcher, and website content that matches the query. It typically shows a short answer plus a small set of nearby practice names, often with addresses or phone numbers attached. ChatGPT does not have a built-in local map layer in the same way; when it recommends providers, it either draws on general knowledge about how to choose a pulmonologist or, when web browsing is enabled, cites specific pages it finds credible, including directory listings, practice websites, and health system pages. This means Google AI Overviews behaves more like a local finder, while ChatGPT behaves more like a knowledgeable friend describing what to look for and occasionally naming options it has read about.
Where each pulls its source material from
Google AI Overviews leans heavily on structured local data: your Google Business Profile fields, review content, and on-page information such as services, insurance accepted, and hours. It also references indexed pages that closely match the searcher's exact wording. ChatGPT's answers come from a mix of general training knowledge about pulmonology and, when browsing is active, from web pages it can access at that moment, favoring content that reads as clear, well-organized, and directly responsive to the question asked. A pulmonology practice's website, blog content, and third-party mentions across health directories and local news all feed into what ChatGPT might reference or summarize.
Which patient questions favor which engine
Symptom-driven, urgent, and location-specific searches favor Google AI Overviews because the searcher already knows they need a pulmonologist and wants the nearest credible option. Queries like "pulmonologist accepting new patients," "lung specialist open Saturday," or "best pulmonology practice near your city" are the kind Google AI Overviews is built to answer with a short list. Educational, comparative, and pre-decision questions favor ChatGPT. Patients asking "how is a pulmonologist different from an allergist," "what should I ask at my first pulmonology appointment," or "is a sleep study necessary for suspected sleep apnea" are still forming their understanding, and ChatGPT's conversational answer format suits that stage better than a short local listing. A practice that only optimizes for one type of question misses patients at the other stage of their decision.
How a clinic can cover both at once
Covering both engines starts with treating them as two different but connected audiences rather than one search problem. Google AI Overviews responds to the same fundamentals as local search: an accurate, fully filled-out Google Business Profile, consistent name-address-phone information across the web, current reviews, and website pages that clearly state services, insurance relationships, and locations. Practices that let their profile go stale, use outdated hours, or accumulate unanswered reviews give Google AI Overviews weaker material to work with, and weaker material means a lower chance of being named in the short list it generates.
ChatGPT responds to a different kind of visibility: clear, well-structured written content that answers the actual questions patients ask before they book. This includes plain-language explanations of common conditions treated (asthma, COPD, sleep apnea, pulmonary fibrosis), what a first visit involves, what tests are typically ordered, and how the practice's approach differs from urgent care or a general primary care visit. When this content exists on a practice's own site and is also referenced or described consistently in other places online such as health directories, local health system pages, or press mentions, it becomes more available for ChatGPT to draw from when browsing or when patterns from training data align with what a patient is asking.
The overlap between the two engines matters more than the differences. A Google Business Profile with detailed, accurate service descriptions helps Google AI Overviews describe the practice correctly, and that same detail, when mirrored on the practice website, gives ChatGPT clearer material to summarize. Consistent information across both channels, rather than two separate content strategies, is what allows a pulmonology practice to show up whether a patient starts with an urgent local search or a slower research-phase question.
Reviews play a role in both systems, though differently. Google AI Overviews visibly incorporates review signals into how it ranks and describes nearby options. ChatGPT does not display reviews directly, but web pages that summarize patient experience, testimonials, or third-party writeups about a practice can still become part of what an AI system reads and repeats when describing the practice to a patient who asks a broader question. A practice that actively manages its online reputation is building material that both engines can use, even though they use it in different ways.
Practices sometimes assume that ranking well in traditional Google search results is enough to appear in both AI systems. That assumption does not hold. A page can rank on page one of classic search results and still be absent from an AI Overview answer, or entirely unreferenced by ChatGPT, because these systems weigh clarity, structure, and directness of the answer differently than traditional ranking signals do. Content written to directly answer a specific patient question, in plain language, tends to perform better across both systems than content written primarily to rank for a keyword.
Every month a pulmonology practice goes without addressing how it appears in AI-generated answers is a month where a nearby competitor's profile, reviews, and content are the ones being read, summarized, and recommended instead. Patients researching a lung specialist today are already asking these AI systems for guidance before they ever open a phone book or a directory site, and the practices that show up clearly and consistently are the ones getting named. The practices that do not are simply not part of the conversation, whether or not they would have been the better clinical choice.