By Lily Chhatwal, Laura Herman, and Bernardo Cantu

Dalberg and UNDavos hosted a senior-level health convening during the World Economic Forum Annual Meeting in January 2026. Leaders from government, the private sector, philanthropies, and multilaterals gathered to examine the future of the sector at a moment of profound transition. Health systems worldwide are navigating fiscal tightening, geopolitical fragmentation, and widening inequities, even as new technologies reshape how care is delivered, financed, and governed amid what is now clearly a structural change.  

Across the discussions, five clear shifts in the prevailing narratives emerged and reframed our understanding of the future of health:  

Volatility is the new normal and leadership needs to adapt 

The contraction of external aid has become the new normal. External health aid to low- and middle-income countries declined by an estimated 40% between 2023 and 2025, with some countries experiencing cuts of up to 70% in essential services.1 As Dr. Tedros Adhanom Ghebreyesus, Director-General of the World Health Organization, stated in his closing remarks, “All of us must recognize that there will be no going back to the way things were. Parts of the global health architecture are being demolished and rebuilt around us.” Stability can no longer be assumed in financing, supply chains, or institutional arrangements. Leaders and their organizations now depend more than ever on their ability to demonstrate financial sustainability amid unexpected circumstances to succeed, and, in some cases, survive. 

For governments, declining aid increases financial pressure while raising expectations for national health spending. As Dr. Leslie Ramsammy noted, countries must “control the narrative, not those who are providing the resources, especially at a time when they are being asked to invest more in health.” This brings the opportunity to set new priorities, and champion those for their constituents. While some funding will continue to dictate terms, as countries raise domestic resources for health, they will be newly positioned to prioritize the issues most important to their local context. 

While countries need to invest more in their healthcare systems, there is also an expectation to shift from donor funding flows to investable opportunities. This means attracting FDI and repositioning the sector as investable, scalable, and commercially viable. This may include expansion of national insurance schemes, government purchase agreements, or use of blended finance to de-risk opportunities. Other examples include economic development zones that come with incentives, shovel-ready sites, and fast-track processes for permitting and licensing.  

Governments will be able to achieve greater agency by strengthening domestic resource mobilization, improving policy predictability, and positioning health as an investable sector capable of attracting capital. At the same time, they must ensure that new investment aligns with national health priorities rather than fragmenting systems further.  

AI is now a part of health infrastructure 

Artificial intelligence has become one of the most important breakthroughs of our time and was the dominant topic in Davos. In 2024 alone, private investment in AI exceeded USD 100 billion, with healthcare attracting more than USD 11 billion.2 Amid this surge of interest and investment, AI is becoming core infrastructure for delivering health services. AI’s greatest value lies in building shared intelligence layers within the architecture of health systems. In practical terms, this means investing in common data architectures, shared models, and governance frameworks so that AI is embedded in how patient data flows, how clinical decisions are made, and how services are coordinated, instead of being mostly focused on a collection of isolated tools addressing scattered pain points. Much like the internet or Wi-Fi, AI is becoming part of the underlying infrastructure of modern healthcare. 

This infrastructure perspective emphasizes that AI creates the most value by turning fragmented data into real-time, actionable intelligence. As Dr. Alex Ng, President of Tencent Healthcare, explained, AI understands patterns at scale and can support frontline decision-making across large populations. In low-resource settings, this translates into strengthening frontline healthcare workers by accelerating triage and referrals, supporting image-based diagnostics, and optimizing workflows. As a result, AI’s impact extends beyond individual applications and becomes a capability that shapes system-wide performance. 

Embracing AI as infrastructure brings greater clarity to how investments should be prioritized and the roles different stakeholders must play. If AI is meant to scale, governments must act as stewards of shared digital foundations, setting standards, ensuring interoperability, and embedding AI into national health strategies. The private sector should design solutions that plug into national systems and can expand sustainably over time rather than create new silos. Finally, it means funders and multilaterals should prioritize durable, system-level investments over fragmented initiatives that deliver quick wins but limited structural impact. 

Business models and unit economics are changing 

Recent advances in AI, cloud computing, and interoperable data infrastructure are leading to faster product development cycles and to leaner teams delivering results more quickly.  

One of the best examples is how start-ups are leveraging these new tools to reach and better understand patients. As Siddhartha Goyal, CEO of Nivi, described, his company is currently having 11 million conversations with patients across five countries. For Nivi, this data represents a living source of information that allows it to better understand patients’ care journeys, needs, and challenges. By mining these conversations, Nivi can segment users, test different messages, and see traction in just a couple of days. What previously would have required substantial marketing budgets and long campaign cycles now costs a fraction and can be run by small teams. This has fundamentally improved the unit economics of engaging patients at scale, enabling more efficient expansion. 

On the other hand, AI is also changing how large corporates operate. Historically, a significant share of their growth has come from acquiring new products and assets. As Shez Partovi, Chief Innovation Officer at Philips, noted, corporates are increasingly investing not only in core products but also in operational and efficiency platforms designed by other innovators to improve their productivity, optimize decision-making, and connect their vast operational functions. In effect, incumbents are beginning to behave more like platforms, plugging external innovations into shared data, workflow, and analytics layers and competing on the strength of these system-wide capabilities rather than on pipelines alone. 

Infertility is not elective care 

Fertility is often treated as a specialized or elective late-stage intervention, yet the discussion at Health@Davos made clear how far this perception is from reality and the ideal scenario. As Elena Méndez-Escobar, Chief Transformation Officer of IVI RMA Global, noted: “One in six people globally experience infertility. In the United States alone, 8 to 10 million people are affected by this issue, yet only around 100,000 babies are born each year through IVF.” 

For years, infertility has not been consistently recognized as a disease, which has led to a disconnect as to how it’s framed and financed within health systems. Despite its deep links to physical health, mental health, and social wellbeing, fertility treatment is usually categorized as discretionary care and, therefore, excluded from standard benefit packages and public budgets. Dr. Randi Goldman of Northwell Health noted that treating infertility as a disease is the first step to challenging policymakers to make reproductive care essential coverage and not a luxury offering. 

Moreover, if we want our health system to respond to the new demographic realities and individual life goals, we need to rethink reproductive care to address the fertility crisis. Currently, our system is designed to think of fertility as late-stage episodic intervention rather than long-term reproductive planning. From adolescence onward, health messaging focuses heavily on preventing pregnancy, while far less attention is paid to helping individuals understand their reproductive lifespan, anticipate future constraints, or act early. We must integrate fertility into population health strategy, supported through earlier information, longitudinal care models, and scalable access. 

Do we really want to live forever? 

As the discussions turned to longevity, a deeper and more human question emerged: what are we actually optimizing for with investments that prolong our lifespan? Much of the public conversation around longevity assumes that extending lifespan is the ultimate goal. At Health@Davos, that assumption was openly challenged. 

Rohini Nilekani, Chairperson of Rohini Nilekani Philanthropies, offered a perspective shaped by culture, age, and lived experience. Reflecting on the growing fascination with immortality, she noted that this aspiration is far from universal, especially among older adults. “When you say you want to live forever,” she remarked, “I suggest you ask the people around you whether they want you to live forever.” For her, and for many in the silver generation, the priority is not extending life indefinitely, but living with dignity, purpose, love, and respect. In her own words, it’s about “putting more life into years, rather than more years into life.” 

At the same time, advances in biology are pushing the boundaries of what may be possible. Maxim Kholin, CEO of Gero AI, shared striking findings from longevity research: “Naked mole rats live ten times longer than rodents of a similar size, and they do not show age-related increases in mortality.” These insights raise provocative questions about whether aging itself can be slowed or even reversed. Yet, as the discussion made clear, scientific possibility does not automatically translate into societal desirability. The challenge for health systems is not only how long people can live, but how to ensure that longer lives are healthy, meaningful, and valued across the full life course. 

In summary 

In the new reality of volatility in the sector, we have an opportunity to deliberately design improved healthcare delivery models for the constraints we face. For governments, this means setting clear priorities, strengthening domestic resource mobilization, and aligning domestic financing with long-term system resilience. For donors and multilaterals, it means investing in institutional capacity, shared digital and data infrastructure, and alignment with national agendas. For investors and innovators, it means grounding ambition in resilient business models and measurable value creation at the system level. And for all actors, it requires recognizing that trust, accountability, and inclusion are not peripheral concerns, but central to realizing the potential that AI holds to improve healthcare around the world.  

At Dalberg, we are working with governments, multilaterals, philanthropies, investors, and private sector leaders to navigate this transition in practice. This includes supporting financing reforms that strengthen country ownership, designing partnership and platform models that enable scale, applying AI responsibly to improve system performance, and advancing life-course approaches to health that prioritize dignity and long-term wellbeing. As global health architecture is rebuilt, the choices made now will shape resilience and equity for decades to come. We welcome continued dialogue on how these shifts may inform your strategy, investments, and operating models in the years ahead.