Modern clinicians are learning to be in multiple places at once. They’re cloning themselves (more specifically, their expertise) digitally.
From longevity pioneers like Fountain Life to visionaries like Dr. Jeffrey Bland and Deepak Chopra, a new wave of practices are building personalized AI companions that extend their clinical philosophy and expertise beyond the visit.
These aren’t generic chatbots. They’re AI extenders: virtual assistants or conversational agents trained on the subject matter expert’s own knowledge, protocols, clinical approach and tone.
They handle the overflow of questions and administrative tasks that typically eat up clinical capacity. At the same time, they help to keep patients tethered to their doctor’s exact approach.
The Emerging Use Cases
Clinics are now experimenting with AI extenders across three fronts:
Patient Education & Follow-Up: Personalized chatbots summarize visit notes, explain lab results, or send tailored health education that mirrors the doctor’s recommendations. Fountain Life’s digital concierge, for example, helps members interpret complex diagnostics and take next steps.
Front Office Operations: Tools like HelloPatient are automating intake and scheduling and answering FAQs with conversational interfaces—reducing staff time while keeping the clinic experience human and responsive. At other practices, some teams are tapping options like Hippocratic AI’s generative AI agents to handle front office tasks from scheduling to follow-ups for patients managing chronic conditions.
Humanized Extensions: Some physicians are taking this further. At a recent conference of top concierge doctors around the country, we heard how a few are using avatar-based video systems that deliver post-visit follow-ups or protocol explanations in their own voice and likeness. These “AI twins” give every patient a sense of personal attention without adding hours to the doctor’s day.
The Upside
Done right, these AI extenders turn static protocols into dynamic, interactive patient experiences.
Patients get clear answers between visits, staff workloads shrink, and clinicians can stay top-of-mind through every micro-moment of care.
It’s the beginning of a new patient-AI-doctor trifecta where patient intuition, AI synthesis, and clinician judgment work in concert.
The Fine Print
Like any tool, this new layer has limits.
Chatbots can hallucinate or misinterpret medical nuance, answering confidently but incorrectly. They can drift into territory that requires real clinical expertise. And even the best-trained models lack true empathy, that subtle, human presence that builds trust and keeps patients engaged.
Also, in many cash pay practices, patients are coming to you for an element of human relationship—not to feel like they are working with ChatGPT.
Where does all of this leave us? In a place where AI needs to be deployed carefully and intentionally. The future isn’t about replacing bedside manner with bots. It’s about extending empathy at scale.
The most successful clinics will be those that blend automation with authenticity, letting AI handle the repeatable while clinicians focus on the relational.
📙 Your Homework: List the top five patient questions or admin bottlenecks your team responds to repeatedly. Now ask: Which of these could an AI extender handle accurately and warmly so your team can spend more time where it matters most?
✴️ Try this: Start small. Train a secure chatbot on your clinic’s FAQs and post-visit materials. Test it internally with your team first to understand the level of risk you’re open to taking on.
How I AI with Andrew Lundquist: Tapping Tech To Put Yourself Out There for Better Patient Relations
On our latest How I AI, we sat down with Dr. Andrew Lundquist, Chief Medical Officer of the Mankato Clinic and Clinical Director at Nabla. He’s been on the leading edge as he and the Nabla team started piloting using AI in practices nearly three years ago.
Dr. Lundquist told us it’s a great time to be in medicine, thanks largely to the increasing range of tools at providers’ fingertips. He’s using them to put himself in a strong position with patients well before they ever walk into his practice.
Dr. Lundquist told about a few specific tools he’s found helpful and his use cases. He walked us through his application of:
ChatGPT: Because ChatGPT is accessible and easy, Dr. Lundquist says he uses it like he used to use Google. He’ll tap it to find information on patients’ condition or to find evidence—though he always checks the sources the AI provides.
Gamma: With this slide/presentation creator, Dr. Lundquist can quickly create external-facing materials that wow. He says he leverages it for everything from communicating with other groups to creating courses.
Lovable: This gives providers a chat-based way to leverage AI to create apps. Dr. Lundquist uses it to create patient information sites that people can query complete with information specific to their condition.
With these resources behind him, Dr. Lundquist has more time to spend on putting himself out there online. He says creating and posting content helps patients come in better understanding him and his approach to things. That, in turn, supports better relationships with those patients.
His philosophy:
📙 Your Homework: Think about the way you present yourself and your practice digitally. Demo Gamma to create an informational slide you can post to LinkedIn sharing your specific expertise.
As a busy clinician, carving out time for what is essentially marketing might feel tricky. Fortunately, as Dr. Lundquist highlighted, tools can help move some other work off your plate. Take Vibrant as an example.
Our all-in-one practice platform is specifically tailored to functional, integrative, and longevity medicine clinics. We combine your EHR with AI-supported workflows like chart summarization and appointment prep.
Interested in trying it out? Get in touch to get started on your own Sandbox environment.
This Week in Clinical AI
Ambient AI scribes slash provider burnout. A study recently followed more than 250 healthcare providers in ambulatory clinics over a span of 30 days. It found that when using an ambient AI scribe, provider burnout dropped from 51.9% to 38.8%.
Patient health forecasting gets a leg up with LLMs. Researchers trained a biomedical large language model (LLM) on real-world EHR data to create DT-GPT, a model that can predict how a patient’s health changes over time. As this technology advances, it could enable true digital twins, giving clinicians a way to simulate personalized treatment responses in real time.
In some areas, AI has already outpaced doctors. Stanford University conducts an annual AI Index Report. Per its 2025 version, AI now beats doctors in diagnostic reasoning. GPT4, for example, scored 92% in diagnostic accuracy, while physicians scored 74%.
New AI technology promises to accelerate research. K-Dense, a new AI scientist from Harvard Medical School and Biostate AI, completed a transcriptomic aging study in weeks, not years. By significantly speeding research cycles, the hope is that this new application of AI can accelerate medical breakthroughs.
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