Where does all of this leave a practicing clinician? As someone who walks the walk of integrative cardiology practice AND physician entrepreneurship, I dug into this question to prepare for my talk at the AIC 2026 in San Diego. I did what I always do: I sat with the data. I read the papers, traced the citations, looked at what was actually happening in clinical settings — not the press releases, not the vendor decks, and not the hype. What I found was not the story of AI triumphant. It was a story of AI unmanaged. And unmanaged AI, in medicine, is not a productivity tool. It is a liability.

I am going to make a claim that may feel counterintuitive, especially if you’ve spent the last year watching colleagues bolt AI tools onto every corner of their practice. Here it is: The physicians who are most at risk of being de-platformed by AI are not the ones who ignore it. They are the ones who are refusing to lead it.

Let me explain.

The Problem Is Not the Tool

At AIC, I will open with what I call Exhibit A. It isn’t a research paper. It is a screenshot: a physician Facebook group post where a community member shared a detailed prompt provided by her patient, instructing others to consider using it. The prompt called for uploading the patient’s lab PDFs directly into a consumer AI chatbot — including the patient’s age, sex, clinical status, and real Cleveland Heart Labs data, with an intent to derive a ‘cardiovascular comparison score for untreated patients in their 60s”. The post got 19 comments, 9 reactions, and zero warnings.

When I asked the physician who posted how she felt about it, she responded by saying that her “savvy patients” were “increasingly using AI to check their care plans, supplement-drug interactions, and even offer some diagnosis for unusual symptoms.” She said she preferred to educate them on how not to get themselves in trouble, rather than “gatekeeping.”

The framing was wrong. Not the instinct to educate — that part is right. But the implicit premise that what her patients were doing was simply an empowerment story. What they were actually doing was uploading Protected Health Information to a platform with no HIPAA Business Associate Agreement, no data retention policy, and no clinical governance. And she, as their physician, retained legal and ethical responsibility for the outcome.

This is not a patient education problem. It is a physician leadership problem. Patients are going to use whatever tools are available to them. They always have. The emergence of “citizen doctors” is a positive externality unleashed by the generative AI radical innovation. What they need from us is not permission — they don’t need our permission. What they need is a physician who has built a system that incorporates AI responsibly, so that the AI their patients encounter inside the clinical relationship is governed, contextualized, and safe.

The Data We Have to Sit With

Let me give you the numbers, because the numbers are worth sitting with.

The first number is the hallucination rate. When Mount Sinai researchers presented large language models with fabricated clinical details, the models elaborated on those fabrications in 50 to 82 percent of cases. They did not reject the false premise. They built on it. They generated highly convincing clinical narratives from thin air.

The second number is the disclaimer collapse. In 2022, AI systems responding to health queries included medical disclaimers in roughly a quarter of responses. By 2025, that figure had dropped to under one percent. The Stanford/Berkeley/UBC preprint found a striking inverse correlation (r = −0.64) between a model’s diagnostic accuracy and the likelihood it would include a disclaimer. The better the model performs, the less likely it is to warn you about its limitations. The safety net is vanishing precisely when the stakes are highest.

And then there is the Harvard Business Review’s eight-month study on AI and productivity — the one that generated a politely uncomfortable finding. AI did not reduce work. It intensified it. Workers absorbed tasks outside their expertise because AI made them feel “newly accessible.” They extended their hours because the cognitive burden of reviewing and correcting AI-generated output required more time, not less. The researchers called it the Productivity Paradox.

In medicine, this is not abstract. The physician who uses a generative chatbot to draft a patient summary now owns that summary. Every error in it. Every hallucination it contains. And the patient who uploads their own lab values to an ungoverned AI system and gets back a fabricated cardiovascular risk score and then shares it with their doc — they are your patient. The liability does not transfer to OpenAI or Anthropic or whoever built the chatbot. It is your responsibility to review the AI slop output-all of its fabricated probabilistic cardiac scoring-and educate your patient as well as provide the deterministic scores and guideline-supported risk estimates, the crux of current cardiac risk evaluation. So this doubles your work and raises your liability.

The Real Displacement Risk

Here is the reframe I want you to take out of this article.

You will not be replaced by AI. That framing — AI replaces the doctor — is a distraction. It mislocates the actual threat. The actual threat is more specific: you will be displaced by the physician down the street who has built an AI-native practice, while you are still using AI as an add-on to a workflow designed in 2015.

There is a critical distinction here, and I will make it explicitly at AIC because I think most physicians have not fully understood it yet. There is a difference between attaching AI to your practice and building an AI-native practice.

ATTACHING AI

Adding tools as a band-aid to existing workflows

Humans still do the heavy lifting, now with the added burden of managing AI output

Creates the Productivity Paradox: more tools, more review time, less actual care

No governance, no feedback loops, no accountability

AI-NATIVE PRACTICE

Workflows redesigned from the ground up around agentic AI capabilities

AI handles the cognitive load of data processing, retrieval, and synthesis

Physicians are elevated to their highest use: judgment, connection, complex reasoning

Governance and feedback loops built in, not bolted on

Attaching AI means you have a chatbot answering patient messages, a transcription tool sitting in on visits, and a summarization widget at the end of the note. These tools exist in parallel to your workflow. When they fail, and they will fail, you catch the failure manually. You are now doing your original job plus reviewing AI output. This is the Productivity Paradox in clinical form.

Building an AI-native practice means starting from a different question: not “which AI tool can I add to what I already do?” but “what would this practice look like if I designed it today, knowing what AI can and cannot do?” The answer requires mapping your actual clinical workflows — not the org chart version, the real version, with all the workarounds and handoffs and hidden judgment calls — and identifying precisely where agentic AI adds value and where it creates risk.

The Framework I’m Using

At AIC I will introduce a framework I’ve been developing for my own practice and for the physicians I work with through Dr.MBA.AI. This framework is called A.G.E.N.T., and I learned of it at the Harvard Data Science Institute Agentic AI In Healthcare course. It is also very convenient given that agentic AI is the paradigm we’re moving toward, but the acronym is genuinely functional:

• Align — Start with clinical outcomes, not AI capabilities. What are you trying to achieve for patients? Design the AI system around that.

• Govern — Establish explicit consent frameworks, HIPAA-compliant data handling, clear disclosure requirements. Governance is not bureaucracy; it is patient protection.

• Empower — Build your team’s cognitive infrastructure before deploying new tools. The skill of critically evaluating AI output — what the researchers call “mindware” — is learnable, but it has to be deliberately taught.

• Navigate — Map your clinical work graph. Identify exactly where AI accelerates value and where AI hallucinations introduce unacceptable risk.

• Trust, but verify — Design graceful escalation into every workflow. When the AI encounters ambiguity or high-risk scenarios, it escalates to a human. Not sometimes. Every time.

What I want to emphasize about this framework is the order. Most physicians start at Empower (what tool do I train my staff on?) or Navigate (where can AI fit in my workflow?). The physicians who are building durable AI-native practices start at Align. They define the clinical outcome first. Then they build backward.

The functional medicine framework is useful here because we already think in systems. We understand networks, feedback loops, and root causes. Those are exactly the mental models required for responsible AI integration. You are not starting from zero.

What the Reframe Actually Changes

The reframe I’m asking you to make is not about AI at all. It is about leadership.

The physicians who are going to be displaced by AI are the ones who outsource the AI decisions to whoever happens to sell them a tool, who treat consent as a checkbox rather than a protocol, who never map their workflows because they don’t have time, who assume the liability is somewhere else. Those physicians are not being replaced by machines. They are being outcompeted by colleagues who understood that AI is a practice design problem, not a software problem.

The physicians who will not be displaced are the ones who refuse to treat AI as a passive tool and instead treat it as a clinical team member that needs to be onboarded, trained, corrected, and governed. Who understand that the competitive advantage is not which AI model you use — every practice can access the same foundational models — but the clinical context you have built around it.

Your longitudinal patient relationships. Your integrative, specialized, longevity or functional medicine systems biology lens. Your specific clinical protocols and values. Your outcomes. The AI model is a commodity. Your context is not.

That is the reframe. Not “will AI replace me?” but “is my practice designed to lead AI, or just react to it?”

In the next article in this series, I’ll show you what that looks like in practice. Specifically: what happened when I ran my first AI build-a-thon for physicians, what we built, what broke, and what I’d do differently.

NEXT IN THIS SERIES FOR PAID SUBSCRIBERS

No. 2 — Build, Ship, Learn: Reflections on Running My First AI Build-a-Thon for Physicians. How we built a functioning supplement storefront in a four-hour live session, what the economics actually look like, and what I learned about physician readiness for AI implementation. Get access to curated resources in Dr. MBA Consulting Community with paid subscription.

His situation is increasingly common in cardiology and primary care. Mid-sixties man with non-obstructive coronary artery disease, with a 50/50 split between calcified and non-calcified plaques on CT angiography. Elevated lipid and inflammation markers, including vascular specific and endothelial dysfunction parameters. He is asymptomatic. He opted out of working with us in 2024. A year later, he still had the same questions, and the same laboratory values. A handwritten scribble on his lab results print out read “LDL less than 100 is good”.

In 2024, he came to us seeking alternatives to statin therapies. His goal was to “reverse high cholesterol naturally.” This ask is so common at the Holistic Heart Centers that we offer a program called Statin Overprescribing Solution to many patients. In fact, my podcast episode on statin overprescribing was the most popular of 2025.

I have received numerous inquiries from physicians as well, with requests to land an integrative cardiology viewpoint to their patient cases. This morphed into our educational platform, Holistic Heart University, with several courses focusing on lipids and metabolism, and a dedicated case review space.

As you could have guessed, his cardiologist already prescribed a high-intensity statin which this patient had no intentions of taking. He, and many patients like him, are quiet quitting their physician recommendations and ditching statin prescriptions, despite seemingly understanding the gravity of their vascular risk. I say “seemingly” because a traditional concept of vascular risk is vague and impersonal, reduced to population-based statistical probabilities, and bearing little to no relationship to patients’ top of mind concerns. Patients are increasingly demanding a personalized solution, seeking alternatives to one-size-fits all treatments.

So I want to let you in on a little secret, completely counterintuitive to what you may be thinking, to help your patients turn their statin rebellion into an opportunity for health optimization.

Read more

In a research abstract at the meeting, investigators reported that an OBSERVATION derived from hundreds of medical records that habitual use of melatonin for insomnia (defined as use for at least a year) significantly increases the risk of heart failure including hospitalization and death.

Since there is no publication, just a poster presentation, it is impossible to know all the biases, strengths and weaknesses of the study but some are glaring.

Key Findings

1. In a large study looking at medical records, those who used melatonin for at least a year were almost twice (2x) as likely to have new onset heart failure diagnosis over the 5 years, and 3.5 times more likely to have heart failure hospitalization.

2. Study is observational, not cause and effect. Patients did not have history of heart failure.

3. Significant study limitations include underreporting by patients, inaccuracies int he EHR data, and the use of melatonin as over the counter supplement except for the UK.

4. Limiting data to the UK and looking at prescriptions data, the risk was still significant at 82%.

5. Is it really melatonin or the insomnia itself? Cases and controls were matched but it is unclear if they were matched for the degree of insomnia or inflammation.

6. Insomnia, and associated circadian sleep disruption impact multiple health domains.

7. Insomnia is an inflammation multiplier, and inflammation is at the core of heart failure, atrial fibrillation and CAD.

8. Taking Melatonin? Lets figure out why you need it, and what actually is happening with your circadian rhythm, sleep and stress.

Here is the study design and the findings with my comments in italics.

Is This A Signal or A Red Herring? See Problems.

The study data was from TriNetX, established in 2013, a growing global network of real-world, de-identified patient data available for research. The study included 130,828 adults (average age of 55.7 years; 61.4% women) diagnosed with insomnia.

• 65,414 participants had been prescribed melatonin at least once and reported taking it for at least a year. Problem: attribution bias. Patients often underreport supplement use, and we all know that medical records are often erroneous, mentioning same medications or supplements even if a patient stopped those.

• A second group of people were examined for comparison (control group) — those who had never been prescribed melatonin and were matched to the group taking melatonin on 40 factors including demographic information, health conditions and medications. Same problem as above: reliance on patient reporting and EHR data is open to inaccuracies as patients often do not consider over the counter supplements important enough to report. Also, in many countries melatonin is over the counter and would not be dispensed by prescription.

The main analysis found:

• Among adults with insomnia, those whose electronic health records indicated long-term melatonin use (12 months or more) had about a 90% higher chance of incident heart failure over 5 years compared with matched non-users (4.6% vs. 2.7%, respectively). Problem: is this melatonin or the insomnia itself? It is entirely possible, even likely that chronic use of melatonin was for severe insomnia which leads to multiple metabolic disturbances and is an inflammation amplifier. It is unknown if these patients were evaluated for sleep apnea, a condition commonly associated with incident heart failure. So the study is akin to seeing ambulances at the scene of an accident and concluding that ambulances cause accidents.

• There was a similar result (82% higher) when researchers analyzed people who had at least 2 melatonin prescriptions filled at least 90 days apart. (Melatonin is only available by prescription in the United Kingdom.) This is better, but having one region substantially lowers the strengths of these findings. While it is by RX in the UK, patients can still get it over the counter including the internet.

A secondary analysis found:

• Participants taking melatonin were nearly 3.5 times as likely to be hospitalized for heart failure when compared to those not taking melatonin (19.0% vs. 6.6%, respectively). Problem: again, is it melatonin or the inflammation due to severe insomnia resulting in chronic use?

• Participants in the melatonin group were nearly twice as likely to die from any cause than those in the non-melatonin group (7.8% vs. 4.3%, respectively) over the 5-year period. Now we really have a problem but again, it is not clear if this was melatonin or the insomnia itself. Likely the latter.

What Should You Do if You Are Taking Melatonin

1. Speak to a trained integrative or functional medicine physician and engage in collaborative conversation.

2. Find the root causes of your sleep disturbance such as sleep apnea: get home-based sleep study! I am testing a home-based device from Empower Sleep, and will report on it later.

3. Address inflammation, oxidative stress, hormonal imbalances, environmental exposures, sleep apnea, excess weight.

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While I cannot make up for the past time, the summer pause brought an opportunity to reflect on a new phenomenon: the emergence of citizen doctors.

Vital Signs

Over the past three months or so, I've noticed an interesting pattern. Patients are using generative AI all-purpose chatbots to interpret their test results and then attempt to cobble up an intervention based on the AI inputs.

I called these patients “citizen doctors” because, just like citizen scientists or citizen policemen, they attempt to engage in the work that requires specialized training, experience, and expertise.

Wikipedia provides a nice review of citizen science, including the origin of the term, its current definition, and the evolution of the citizen science role. There is a typology to citizen scientists, with the most recent definition in activities described in 2022 as “co-creation and participatory approaches” and “contributory citizen science.”

Here are a few notable “citizen doctors” examples:

A 73-year-old man with CAD and ischemic cardiomyopathy (received stents and a defibrillator):

“Hi Dr. Druz,
ChatGPT identified several imbalances in my stool, so I would like to follow up when you are ready: absence of Lactobacillus, low Bifidobacterium, Candida overgrowth, low short-chain fatty acids (SCFAs), and reduced pancreatic elastaseâ?? Related to the 28-day course of amoxicillin I completed in May? Lowering beneficial bacteria and opening the door to yeast overgrowth and reduced gut fermentation? I welcome your help and wonder about enzyme/antifungal support. Thanks and warm regards.”

A 49-year-old woman with cryptogenic CVA due to PFO, idiosyncratic reaction to an antibiotic, and/or Eliquis with transient elevations in liver enzymes after the PFO closure procedure:

“After stopping ALL medicines (except metoprolol) and supplements, AST-ALT returned to normal, but in analyzing historic and very recent bloodwork, I see consistently high MCV and MCH, low RBC and RDW, and high ferritin. This, coupled with my history of PCOS and high cholesterol, makes me wonder about NAFLD and the benefit of a high-impact intervention like metformin (also high glycaemic protein)? Did we also test for hemochromatosis? I am trying to connect the dots! Thank you!!”

Bottom Lines

Generative AI is a radical innovation. Radical innovation is often used in a business or technology context to describe technology or a process that is fundamentally different from the current state and offers transformation through disruption.

I found this definition from “Digital Leadership” to be helpful:

“Radical innovation is a term that encapsulates a groundbreaking and transformative form of innovation. At its core, the definition of radical innovation lies in its departure from incremental improvements or minor modifications. Instead, it represents a profound shift in thinking, technology, or business models. This type of innovation introduces entirely new concepts, products, or services that challenge existing norms and redefine industries. The radical innovation meaning is characterized by its disruptive impact, creating a significant departure from the established status quo. In essence, radical innovation is not an incremental enhancement but a revolutionary leap, paving the way for novel solutions, approaches, and opportunities.”

In using generative AI, patients are radically innovating on the traditional process of medical testing and healthcare delivery by taking a shortcut to fulfill their jobs. To fully understand jobs, pains, and gains, and how those shape the emergence of innovative technology or process via products or services that are gain creators or pain relievers, check out the value proposition canvas on Strategyzer.

What often does not get discussed is that radical innovation produces both positive and negative externalities. Externalities are essentially unintended consequences. These terms are most often encountered in economics to explain how activity in one part of a business may produce an unexpected cost or benefit somewhere else outside of a company. Investopedia defines an externality as “a cost or benefit caused by an economic actor that is not suffered or enjoyed by that same actor.”

Generative AI's positive externality is enabling patient agency and access to test results interpretation. But a much more significant negative externality is a breakdown in the medical thinking process and violation of the checks and balances that underlie diagnostic and treatment decisions. This negative externality enables cognitive bias (Dunning-Kruger effect), where “citizen doctors” lean out of co-creation and collaboration, and lean in to shortcuts that will end up taking many down irrelevant rabbit holes.

Fortunately, my patients did lean into collaboration. I believe the significant positive externality of these generative AI experiences is patient engagement with a trusted physician…of course, provided that they have one who is willing to engage comprehensively and collaboratively.

What do you think? What have been your experiences? Please drop a comment and let’s discuss!

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One thing is clear: the beginning is hard!

There is so much I want to say… but where do I start? I am pretty good at conversation, but writing is an entirely different medium. And there is no use of ChatGPT for this!

1. Why this, and why now

Plants and humans grow in spurts. There is seasonality to our growth. For many mid-career physicians, including myself, the “mid” season is not about a growth spurt, but rather stagnation. One begins to question their purpose. Clinical work becomes repetitive and uninspiring. There is a longing for something else, something bigger than the daily grind…

This is not burnout. This is a call to action. And if you are willing to head it, you may end up doing things that you have never thought of, like completing an executive MBA at 53. Founding a company. Radically shifting your mindset.

This is the real reason beyond “Vital Signs and Bottom Lines”. I want to take you on an experiential journey of discovery. Come along to explore the intersection of healthcare with disruptive technologies and evolve in your entrepreneurial thinking. Open your “third eye” to see the future.

2. What kind of community would I like to build here

The speed of innovation is astounding. The amount of healthcare data is doubling every 73 days globally. Patients have become consumers, and now, with generative AI tools, they have become “citizen doctors”. If you are excited about the possibilities that this data explosion and health digitization can bring to improve and optimize our healthspan and lifespan, and perhaps a bit anxious about it, then this is the space for you.

3. What you may expect from this Substack

I will be posting every few weeks. The posts will always have two key sections:

• Vital Signs: reflections on the value and benefits of companies, services, and technologies that are reshaping healthcare.

• Bottom Lines: a business case-like analysis and entrepreneurial takeaways.

• Many posts will be free.

• Posts for paid subscribers will be in-depth case studies, complete with strategic, operational, and financial discussions. You can think of them as a mini-MBA series. These posts will have interactive features, including discussions.

Let’s get started!