Consider the US healthcare programs, Medicare and Medicaid.

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Some 65,748,292 million are enrolled in Medicare; and 74,640,222 are enrolled in Medicaid. (Some 12.5 million are enrolled in both). This comprises three of every eight Americans.

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This is a mass market for healthcare services. Yet what individuals want is not to be a faceless item in a faceless crowd. They want to be a ‘market of one’ — myself. Each individual has complex needs and vast personal data. They want to be seen, recognized — and served appropriately.

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Some 3 million people are employed in healthcare in the US — professionals, administrators, all told. This makes barely 2 % of those served. Surely it is not feasible to provide customized, individualized service for this market? One personal-care physician may have a thousand clients or more.

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Few personal records are more sensitive than those related to health and well-being. Few public services demand bias-free care more crucially than healthcare. How can the tiny army of administrators individualize healthcare services? At the same time, stem the rapid rise in healthcare costs that now consume some $5 trillion or $15,000 per person, 18 percent of GDP, while ensuring privacy and inclusion.

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Thus, Healthcare can become a market of one — provided the AI platform meets the requirements.

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What are those requirements? First, standard ones: bias-free, transparent, secure. Second, personalized.

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“How’s your pain, from one to ten?” Until AI, that question was often the only “personalized” assessment of pain when diagnosing a patient.

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Asking someone to rank their pain exemplifies the core issues in modern healthcare — patients respond in the context of their previous experiences and doctors judge the responses differently depending on bias.

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Today, AI has the power to analyze language by analyzing facial expressions and understanding natural ups and downs in pitch and tone. The ability to communicate the unspoken from patient to doctor has the potential to eliminate bias and increase the speed and accuracy of diagnoses.

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Not only can AI can address current challenges in healthcare but it has the power to shift the focus from reactive to proactive care and fundamentally transform the US healthcare approach. For instance, AI-driven analysis of X-rays and scans can detect early signs of cancer, enabling treatment before the disease progresses.

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AI can also assist in patient management by answering simple post-procedural questions, reducing the burden on healthcare professionals and improving patient satisfaction. Moreover, AI-backed platforms can centralize support for specific life transitions, such as new parenthood, puberty, sex education, and menopause, providing tailored guidance and trusted resources.

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By predicting health issues before they become critical, AI can help keep people healthier, productive, and engaged in society, reducing stress on both patients and providers. This proactive approach has the potential to help Medicare and Medicaid not only save money but strengthen the broader public healthcare system by reducing the demand for expensive treatments and alleviating burnout among doctors.

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While AI has the power to revolutionize healthcare, it comes with some serious risks we can’t ignore. Take the UnitedHealthcare data hack earlier this year — hackers managed to steal the personal and health information of a huge number of Americans, showing just how vulnerable our data can be when technology is involved. But that’s not the only concern. There’s also the issue of bias. If AI is trained on data with historical biases, it could end up making skewed decisions, leading to unequal care for certain groups. And let’s not forget the human element — over-reliance on AI could mean doctors start to trust algorithms too much, potentially missing the nuances that come from direct patient interaction. Plus, the complexity of these systems can make it hard to know exactly how decisions are being made, leaving both patients and providers in the dark. So, while AI holds incredible promise, we need to tread carefully to avoid these pitfalls.

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Providers of private goods and services long ago embraced markets-of-one. Governments have been slow, understandably, given the difficulties. Now, AI can step up to help. The resulting improvement in the quality, quantity and cost of public services, especially the 800-pound gorilla, healthcare, will be huge.

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** Pine and Gilmour. The Four Faces of Mass Customization. Harvard Business Review, Feb. 1997.