Handle With Care: AI Health Guidance and Considerations for UHNW Individuals and Global Leaders

Dr. William Lang: Two things: the scale of what's at stake, and the fact that these are lives constantly in motion. The people I care for rarely live one life in one place — they're running companies across time zones, sitting on boards all over the country, and typically, both the principal and their family are spending part of the year abroad. So, care that is delayed or deferred because someone is not near their home physician is not just inconvenient: A missed diagnosis or a delayed referral can impact a transaction, a succession plan, a company's leadership continuity. That's why our clients find it so valuable to have a physician who already knows their history and that of their family members and is reachable the moment a medical question or issue comes up.

Ghonche Alavi: There is also a data dimension that most people never weigh. Large organizations invest heavily in cybersecurity controls, but no one can ever guarantee that data, once entered into a third-party platform, won't be accessed and then leveraged. With ultra-high-net-worth individuals and executives, that is always the concern — the motivation of a threat actor, and what they would do with the data. So, a question that feels like a quick, private convenience is rarely either, and at this level, you really have to think it through before you disclose. 

Dr. William Lang: I want to differentiate between consumer use and physician use of medical AI. For consumers, AI can be very useful for education and orientation, and it is fast and easily accessible. These models pattern-match across enormous datasets, and much of it is generic health content written for the average consumer. Most current generative AI models are rarely wrong in dramatic ways, but in quieter ones. However, in medicine, AI’s convenience carries a cost because these tools lack the training, judgment, and accountability of a licensed physician, and misuse can have serious health consequences. I tell patients to use it to ask better questions of their physician and to become better, more informed partners in the decision process.  

On the other hand, medical professionals use AI to identify things they may not have considered and to help weigh risks and likelihoods of various diagnosis and treatment options. In these cases, the AI provides a starting point and links to appropriate authoritative professional sources almost instantly. But for making diagnostic and treatment decisions, especially in an urgent situation, it is best used as a tool for a physician and has no business standing in for a physician. 

Ghonche Alavi: What strikes me from the privacy side is that the potential inaccuracy and the exposure compound each other. Someone gets an uncertain answer, so they go back and add more detail to try to get a better one — perhaps they add more symptoms, more personal history, more identifying context. The richer and more personal the prompt, the more useful the answer and the more sensitive the data trail left behind. So, the two risks inevitably rise together. 

Dr. William Lang: AI is an extraordinary force multiplier for someone who already knows how to ask the right question and verify the answer. But diagnosis is not about symptoms alone; it is about context. It turns on history, such as past illnesses, medications, family risk, or some type of nuance that changes everything, and much of a physician’s training is simply knowing which of those pieces matter. Interpretation is harder still, because medical recommendations are rarely clean: they weigh risks against benefits relative to the circumstances of one particular person.

AI also bears no accountability for the outcome, its training may be dated, and it can carry bias that underserves certain populations. The step people skip is returning to the source to confirm the answer holds up; they treat the output as a conclusion rather than a starting point. Good medical decisions depend not just on information, but on information informed by detailed facts and circumstances and then knowing which ideas and recommendations matter.

Ghonche Alavi: And trust runs in two directions at once — the accuracy of what emerges and the security of what goes in. A non-expert cannot validate the sources even when cited, and the model lacks the full history, so gaps are inevitable. The security half is the one people underestimate. Most users simply don’t know what questions to ask, such as: where is the data stored, under whose laws, is it encrypted, and could it be used to train future models? With personal health data, each unanswered question is an open door to risk.

Ghonche Alavi: Data grows more valuable the more identifiable and prominent the person attached to it is. Medical information is among the most sensitive there is, and before you enter it into an AI chat, you should ask three questions: Where is this data going? Who can access it? How will it be used? The harm rarely begins with a single disclosure — it accrues as you go down the rabbit hole. One question prompts another, and before long, your age, your physician, your laboratory results are all on the record.

I think of every platform as an attack surface — one more point where information can leak through a breach, whether that’s an employee with the wrong access or a vendor's vendor. Few people treat a chatbot conversation as "data" the way they treat a bank statement, but functionally it is — only created more casually, at eleven at night, without a second thought. Furthermore, because the account is usually tied to a credit card and an address, a breach can reconnect supposedly anonymized queries to a name. Those breadcrumbs can be assembled for impersonation, extortion, reputational damage, or a physical-security threat. The data need not even be misused to cause harm; sometimes its mere existence outside your control is the harm.

Dr. William Lang: And that is where the privacy concern becomes a clinical one. A leaked diagnosis can be turned toward extortion, a reputational attack, or leverage in litigation. I have watched families take real measures to keep a condition private, only to have it undone by one offhand exchange, either in real life or with a chatbot. There is a subtler version, too: ask the same question often enough, and the system begins to associate the subject with you. My wife and I were researching a cruise, and weeks later the tool volunteered a reference to the very destination I had asked about. Now picture a prominent figure pressing a chatbot repeatedly on a sensitive health issue — an association forms, and no one can say where it travels. A physician who holds your full history, by contrast, can name the detail that matters, and a physician's own queries are too varied to attach to any single patient. The reassuring part is that protecting yourself takes only a few habits.

Ghonche Alavi: A handful cover most of the risk, such as:

• Avoid entering personally identifiable details.
• Use trusted, secure platforms rather than whatever is at hand.
• Read enough of the privacy policy to know where data lives and how it is used.
• Resist supplying a detailed medical history.
• None of these habits require becoming an expert. Instead, it’s about treating the convenient option as the consequential one it can turn out to be.

Dr. William Lang: Speed is valuable only when paired with judgment, never as a substitute for it. That is the model we operate under in executive medicine: a physician reachable immediately, who already knows your history, your medications, your risk factors, your last set of labs —  the speed of AI with the judgment of a relationship built over years. What you do not want is an answer in three seconds from a source that has no idea who you are, what you are allergic to, or what you asked your endocrinologist six weeks ago. AI grants a head start, but it is a point of departure, not a conclusion.

Ghonche Alavi: There is a privacy version of that same trade-off. Speed in a consumer tool usually means the path of least friction — fewer settings checked and fewer questions about where the data goes, because slowing down to read a privacy policy defeats the whole point of asking quickly. The very thing that makes a tool feel fast is often what makes it uncontained. So “fast” cuts against careful judgment on both fronts at once — clinically and on the data side. Ultimately, the best model is not AI or a trusted advisor, but AI disciplined by both — executive medicine and data privacy expertise under one roof, pairing the speed of AI with the judgment and protection it simply cannot supply on its own. 

Learn more about how Crisis24 Private Strategic Group offers immediate access to world-class medical care and support worldwide as well as advanced cyber risk reduction and incident response tailored to your family’s lifestyle and risk profile.