A new model of healthcare for the developing world

I believe that the future of healthcare could start where access is most limited. Here’s why (and how).

Developing countries have a unique opportunity to leapfrog the traditional model of healthcare and move directly into its next evolution:  a healthcare system that shifts from a labor-intensive model to an AI-native one, where the precious time of human clinicians is allocated to the most complex cases and where AI executes a significant portion of the work on autopilot.

The systems that developed societies built over the last few decades have become structurally limiting. They’re organized around physical proximity, finite clinical hours, and infrastructure that doesn't scale. Those building today from the ground up don't have to inherit those constraints. 

I know that this sounds utopian (and somewhat naive) but it’s happened before, just in a different realm. 

Take African landlines as an example. By the time the continent was ready to address connectivity, mobile already existed. Installing traditional copper landlines at scale would have meant digging trenches across thousands of miles, negotiating right-of-way through villages without formal addresses, and maintaining lines exposed to weather and time. It would have been decades of work and billions in installation capital, plus infrastructure that was extremely difficult and costly to maintain. 

Mobile required none of that. A single tower could cover what would have taken thousands of poles; installation took days compared to decades of road-building to support copper. The capital required to cover a region dropped by an order of magnitude. Today, many African countries have more mobile subscriptions than people. Fixed-line penetration never cleared single digits and never will.

The same logic can be applied to healthcare.

The traditional healthcare system is the equivalent of copper. It requires 1:1  appointments and all of the infrastructure that comes with it: hospitals, clinics, specialists, administrative teams, call centers, scheduling, insurance, physical proximity, and a massive clinical workforce. It is slow to build, expensive to maintain, and impossible to scale fast enough to meet demand.

For developing countries, pursuing that model would mean spending decades building a system that developed countries are already struggling to sustain. 

Therefore, and in a paradoxical sort of way, the existing healthcare problem in developing countries also presents an opportunity. Given that there is no deeply entrenched status quo, or incentives that hinder change and stifle the full diffusion of AI in healthcare, developing countries can accelerate adoption and build an AI-native healthcare system from the ground up.

The first question is where to start. I believe the first pillar of this AI-native healthcare system should be a national health hotline. Before a country builds hospitals, clinics, digital records, specialist networks, and complex care pathways at scale, it needs one universal front door into the healthcare system - a fast, effortless way to understand what is happening, assess how urgent it is, and guide patients to the right next step.

The NHS 111 model is an important precedent here. NHS 111 was created to give people a simple, memorable number to call for quick, easy access to medical help. 

That same concept becomes even more powerful in a country without mature healthcare infrastructure. A national health hotline does not require every village to have a clinic. It does not require every person to know which specialist to call. It does not require the population to navigate a fragmented system that does not yet exist. It only requires a phone, a number people can remember, and a clinical intelligence layer capable of understanding symptoms, assessing urgency, diagnosing, prescribing and, if necessary, guiding people to the right next step.

That’s the ideal starting point for an AI-native health system. It becomes the first layer of care. The place where people go before the hospital, before the clinic, before the specialist, and before they are left alone trying to decide whether something is serious or not. It can immediately resolve low-acuity needs, identify urgent cases earlier, route people to scarce clinical resources more efficiently, and create a national map of demand in real time.

In developed countries, health hotlines were created to help overloaded systems manage complexity. In developing countries, an AI-native health hotline can do something even more important: become the foundation upon which the entire AI-native healthcare system is built.

It is the fastest, cheapest, and most universally accessible way to give an entire population a front door to care.

The AI industry needs undeniable examples of how AI can improve humanity at scale. Right now, those examples are too few. As one of the leading AI health companies in the world, we feel a responsibility to turn that promise into reality through real impact in the field.

Our AI Care platform has already served more than 1 million patients across the globe, enabling immediate access to high-quality care in what feels like a magical experience.

Predicated on this experience, we are well positioned to create one of the first large-scale examples of AI being used not to improve enterprise productivity, optimize advertising, or generate (unsavory) content, but to expand access to healthcare for people who would otherwise have little or none.

AI, after all, can and should be used for the good of humanity. At Sword, we’re ready to deliver it.

Ok, but if we’re ready to deliver it, then why am I writing these words here instead of, well, delivering it right now in developing countries around the world?

Because technology alone is not enough.

Take the example of our work with the Greek government on this use case. In order to make it a reality, it was critical to work in deep partnership with the people who understand the realities of healthcare access in the country, who know where access breaks down, which populations are most underserved and what prevents people from getting the care they need.

That understanding is essential because it’s naive to think that AI alone will magically solve healthcare in a developing country. But with the right local knowledge, partners, and operating model, I believe we can build in years, or in some cases even months, what would otherwise take decades.

This is where the combination becomes powerful.

Sword brings the technology and our vast experience on how to move healthcare into the future with AI. The right organization brings the context: trust, local access, institutional knowledge, government relationships, and a clear understanding of the communities that need this most.

Together, this creates a much more efficient path to adoption.

The developing world is not one market. It is a complex set of countries, communities, constraints, and realities. The right partner understands how healthcare actually works on the ground, who people trust, where access breaks down, and what it takes to make the technology work for the people who need it most.

So, if you’re an organization that understands the idiosyncratic needs of developing countries and you feel as passionate about this as we do, reach out. Let’s do something together.

If we get this right, this will not just be a good use case for how AI can improve humanity. It will have a real and lasting impact on millions of lives. People who will have a future because they had access to healthcare when it mattered most. Millions more lives that will unlock their full potential because health is no longer dragging them down.

Of all of the work to be done in AI and healthcare, this is the kind that inspires us most.