AI won't fix American healthcare by itself, but it can help us close the gap

The United States spends more on health care than any other country, almost twice the number of other developed countries. However, our results are consistent. We face higher maternal mortality rates, lower life expectancy, and shocking differences in care based on race, geography, and income.

It's no secret that the system is broken. But what is often overlooked is that we now have to do something about it with the help of artificial intelligence. AI alone will not repair health care in the United States. But when applied responsibly, it can help us increase access, reduce costs, and ultimately save lives.

A tight system at the seam

Healthcare workers are burned down, administrative expenses are surging, and patients in rural or low-income communities often wait for weeks or months to get basic services. Those with chronic or behavioral health needs, especially underserved populations, are most likely to fall into the risk of falling into the cracks.

At the same time, we see a wave of innovation in AI that can fundamentally change the way we care. In 2024 alone, globally, more than half of this has been invested globally, with more than half of it being used for AI-powered solutions. But unless these tools are built to address the real gap in access, efficiency and improving patient outcomes, we can strengthen the same whole body failure by simply using smarter code.

AI’s commitment in practice

At Techstars AI Health Baltimore, a new accelerator was launched in partnership with Johns Hopkins University and Carefirst Bluecross BlueShield, and I have seen it possible when AI is applied intentionally.

Using Embryoxite, a startup that develops non-invasive preimplantation tests that predict the likelihood of pregnancy during IVF. Their AI analyzes data from embryo culture media to provide personalized insights to help patients and providers make smarter fertility decisions. This can greatly reduce the financial and emotional burden of fertility care and make it easier for families who otherwise cannot afford the repetitive cycle.

Another example is AIDOC, an AI health company that doesn’t fit our accelerator, but instead has done a transformative work on clinical decision support. Their platform helps radiologists and nursing teams prioritize critical cases by labeling abnormalities in medical imaging in real time, simplifying workflows, reducing diagnostic delays, and ultimately improving patient outcomes in emergency rooms around the world.

These are not assumptions. They are real-life examples of AI already deployed to improve health outcomes, reduce waste and expand care, especially where the system fails.

Why must care be obtained in the center

AI’s success in healthcare won’t come from building shiny new tools for systems that already have good resources. It will come from the confusing, underfunded and underserved parts of embedding innovation into healthcare and design with these communities.

This means training models on various datasets and validating tools for multiple patient care (such as community health centers and large health systems). This also means ensuring that startups have the guidance and clinical partnerships needed to build something that is practically effective for patients and providers.

Baltimore is one of the best examples of this approach. This is a city with world-class institutions, real health challenges and committed to building equitable solutions. It is also more affordable, more cooperative, and more rooted in reality than many traditional technology hubs.

A smarter path forward

Healthcare will never be “fixed” by technology alone. But we can’t ignore the possibilities of AI: faster diagnosis, smarter workflows, better use of limited resources, and more personalized care.

To get there, we need more public-private partnerships. We need investors to support startups that solve real problems, not just glossy demos. We need founders who are as passionate about influence as innovation.

If we do that, we can build a system that is better for everyone, not just one that affords concierge services or lives near major medical centers. We can close the gap between what we spend and what we get. We can move from pathological care to intelligent, proactive health care.

AI won't save us. But this can help us ultimately achieve the promise of a system that is suitable for patients, not just profits.

Photo: Dilok Klaisataporn, Getty Images

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