Consumers and powerful advances in AI are transforming healthcare

• PwC’s Global Health Report examines five key trends shaping the future of the industry. Among the findings: AI will become a form of infrastructure transforming healthcare by embedding predictive, proactive care into workflows.
• As data liquidity rises as a priority, it will be vital to enable secure, interoperable, real-time sharing across systems, while ensuring privacy and cyber resilience.
• Consumer-driven care models are on the rise, blending wellness and healthcare with decentralised, digital-first services focused on prevention, affordability, and continuous well-being.

Two very powerful vectors are reshaping the global healthcare market. The continued growth and power of AI, digital technologies, and data are reshaping every business—but have a particular salience in healthcare. And around the world, more people are taking an active interest in the way they access health products and services. As consumers become more empowered by the data and technology available to them, the delivery of care is becoming more decentralised and personalised. What people expect from the healthcare system is shifting from reactive care and treatment to proactive services that enhance both the length and quality of life.

Add it up, and the stage is set for significant structural change and integration. PwC’s Global Health Report looks ahead at five of the key trends shaping the sector in 2026 and beyond. For each, we identify the strategic imperatives and implications for organisations seeking to claim competitive advantage in this rapidly shifting environment. Those that thrive won’t simply layer technology onto legacy models. They will redesign care pathways, methods of drug discovery, payment mechanisms, governance models, and workforce structures around prevention, prediction, decentralisation, and measurable outcomes. They will harness the powerful technologies on offer to meet people where they are—empowering them to reach their best health outcomes.

The question about AI in healthcare is no longer whether to adopt. It’s how to do so most effectively. Looking ahead the difference makers will be those organisations that use the technology to improve fundamentally how they plan and prioritise care and deliver it at scale. AI must become integral to the operating model rather than layered on top of it to deliver meaningful results. AI’s value will increasingly be judged by its impact on patient-centred outcomes and system performance rather than simply the number of tools deployed.

Re-engineer care around prediction, not reaction. Today, most healthcare AI is deployed against discrete, well-bounded tasks such as documentation, diagnostics, and scheduling. Transcription tools are displacing manual notetaking, while AI-supported coding and rostering are reducing administrative bottlenecks, freeing up clinician time, and contributing to improved patient outcomes. But now the focus will shift to prevention and better coordination across functions. AI will increasingly operate before the clinical encounter, moving beyond back office administrative work. Rather than responding to deterioration once it becomes visible to clinicians, systems will increasingly alert caregivers to problems and prompt them to act earlier. The result? Reduced avoidable admissions, length of stay, and downstream pressure. Essentially, AI will shift from a decision or support tool to a mechanism for continuous clinical risk surveillance. Machine learning and data analytics technologies are already improving children’s cancer treatment by predicting the likelihood of relapse and assisting clinicians in making more informed decisions with unprecedented breadth and accuracy.

Reshape the workforce model. Workforce availability has been a constraint on the pace of many advances in health, such as tech-enabled care, behavioural health, and physician-led speciality platforms. When AI is embedded in core workflows and operating models, its impact on the workforce becomes structural rather than an incremental productivity add-on. It enables growth without proportional increases in labour. Clinicians won’t be replaced, but their work will become more supervisory and judgment-based. For example, they will oversee algorithm-generated risk signals, validate recommendations, and focus on complex decision-making. Making the most of such efforts will also require upskilling and innovations in the way clinicians are trained. As PwC’s US Deals 2026 outlook for health services finds, platforms that demonstrate measurable performance through AI-enabled operations are better positioned to expand capacity, standardise care, and absorb demand volatility.

Build the capacity to manage demand proactively. For many health systems, the primary capacity constraint will no longer be beds or workforce, but algorithmic capacity. That is, the ability to process data in near–real time and translate it into beneficial action. As generative AI becomes widely accessible, unmanaged and informal use is increasing faster than organisational capability to govern it. We will see a growing divide between organisations that actively define how AI is used in clinical and administrative workflows and those that allow fragmented adoption with unclear accountability. Systems that can ingest and synthesise signals from clinical records, devices, and operational data will create more time for professionals and accelerate clinical research. Systems that can’t will remain locked into reactive care models, regardless of how many AI tools they deploy.

Overcome the human barriers. Challenges in building trust and addressing privacy and ethical concerns remain among the most difficult barriers to AI adoption, followed closely by workforce education and resistance to change. These human factors now outweigh technical barriers such as data quality or outdated infrastructure. Clear governance, explicable AI, and transparency about how models operate are essential to building trust. And they must be supported by emerging frameworks and guidance requiring standardised assessment of bias in AI data, outputs, and use to ensure equitable outcomes.

AI at scale depends on one critical enabler: data that can move, be trusted, and generate insight across the health system in real time. Today, clinical records, imaging, claims, genomics, device data, and patient-reported outcomes often sit in silos due to organisational, technical, or regulatory boundaries. That limits their usefulness. Engineering and synthesising this data into assets that can support clinical decision-making, resource optimisation, and improved care outcomes is a significant challenge. Going foward, as PwC’s The future of healthcare providers report finds, the focus will be shifting from collecting more data to making existing data liquid: usable, shareable, and valuable across clinical, operational, and consumer contexts.

From data accumulation to data value. Data liquidity isn’t about removing controls or centralising everything. It’s about enabling data to flow where it creates value, under the right permissions and safeguards, while democratising access to appropriate data to support innovation and AI-driven advancement. Leading organisations are increasingly treating data as a managed asset, focusing on how it’s captured, governed, integrated, and translated into action. AI, predictive analytics, and personalised care all rely on timely access to high-quality, interoperable data. While robust safeguards govern the use of data, public confidence in data sharing is often low. According to PwC’s 2025 Global Digital Trust Insights survey, only 24% of healthcare leaders say they are confident in compliance with privacy regulations, and just 19% express confidence in AI regulation compliance. Leaders will have to apply high-quality, well-governed data foundations with consistent standards and data hygiene. They must set the conditions under which data can be moved and used.

Integration and interoperability across care and life. Health data is now generated continuously through wearables, home monitoring, digital therapeutics, and consumer platforms like retailers. Individuals now have access to health insights at a pace and scale not previously possible, including from smart watches and smart jewellery. The task for health systems is to integrate insights safely and proportionately into electronic records and everyday clinical workflows, and then to provide actionable insights. Instead of simply telling people they aren’t getting sufficient sleep, physicians can offer details on how to rectify the situation.

Healthcare systems are increasingly expected to support data portability, for example, through OpenAPIs, as part of both regulatory compliance and safe digital transformation. Organisations that invest in interoperability and strong data governance are better positioned to meet these expectations, while also enabling more secure use of AI and more effective care delivery. Initiatives such as the NHS Federated Data Platform in the UK reflect a growing need to integrate disparate datasets across health services organisations, addressing long-standing fragmentation within the health system.

Security, privacy, and governance. Real-world data supports research, outcome-based contracts, population health management, and new partnerships across the value chain. But realising value depends on trust and control. Liquid data must be secure data. Yet while cyber risk remains the top mitigation priority for more than half of healthcare leaders in PwC’s 2025 Global Digital Trust Insights survey, only 2% report having fully implemented cyber resilience actions across their organisations. This gap is material.

Leading organisations are embedding security, privacy, and governance into data architecture from various providers in the ecosystem at the outset rather than treating them as constraints added later. This includes clear data stewardship, role-based access, auditability, and continuous monitoring. PwC’s Strategy& From MedTech to WellTech study suggests that while people are broadly open to digital and well-being technologies, data security and use remain significant concerns for over a third of respondents. Health systems therefore need to convince patients of the efficacy of these technologies through transparent consent models, clear value exchange, and simple explanations of how data improves care.

Over the coming years, consumers’ choices will increasingly determine which healthcare models scale, and which are left behind. The distinction between consumer wellness and traditional healthcare is becoming increasingly blurred. In reality, all patients are now consumers. They compare experiences, expect seamless digital access, and judge healthcare against retail, banking, and technology platforms. PwC’s 2025 US Healthcare Consumer Insights Survey found that 70% of people now use health technology such as wearables, apps, or virtual services on a monthly basis, and 65% want a system built around prevention rather than treatment.

Design services around where people live and work. The same survey found that while 72% of people received care in a doctor’s office in the past year, only 34% say that would be their preferred setting in the future. Virtual care, retail clinics, and at-home services are increasingly seen as default options, particularly for routine, follow-up, and preventative care. And there is a rising expectation that care should take place beyond scheduled appointments. One in five people say they would pay more out of pocket for personalised treatment, continuous monitoring, or unified digital platforms.

Traditional models generate value on a cost-per-encounter basis, tied to physical capacity and episodic activity. In contrast, consumer-orientated models support continuous management, prevention, and earlier intervention. They align revenue and incentives more closely with measurable outcomes, maximising lifetime value per person through scalable, digital-first platforms operating across home, community, and virtual settings.

Simplify systems, and make them more affordable. Everyone in the system—caregivers, insured people, uninsured people—faces challenges of access and complexity. A larger proportion of our population now identifies as caregivers. They often support children or ageing parents and experience higher barriers to access, greater cost anxiety, and higher unmet need. Among uninsured people, over half report a healthcare need they aren’t addressing due to affordability. Even insured people express concern about uncovered costs, emergency care, and long-term conditions. These pressures are pushing people to seek simpler, more coordinated solutions, i.e. one system rather than multiple apps, portals, and providers. Yet only 26% of respondents in the survey say it’s very easy to access their medical records across providers. Fragmentation disproportionately affects those with lower health literacy, limited digital access, language barriers, or less time to navigate complex systems. For lower- and middle-income countries, the implications are even more pronounced. Where physical infrastructure and specialist capacity are constrained, scalable, digital-first, and community-based models offer a way to extend access without replicating high-cost hospital-centric systems.

From treatment to continuous well-being. People are increasingly engaging with tools that track, test, and tailor health outside traditional care settings. The same survey shows that nearly 80% of Gen Z use health technology monthly, and they are significantly more willing than older cohorts to trust non-traditional entrants such as technology or retailers. Across the US, UK, and Europe, this broader ‘well-being technology’ market is estimated to represent up to US$850 billion annually, largely driven by consumer demand.

Importantly, people aren’t asking for technology to replace clinicians. They are most comfortable with digital tools handling navigation, monitoring, and administrative coordination, freeing clinicians to focus on diagnosis and treatment. When well designed, these tools can also equip individuals with clearer and more relevant information, enabling more informed and constructive engagement with clinicians about their health and care options.

The twin trends of bringing care closer to home and shifting towards value-based models will increasingly reinforce each other. The challenge for leaders isn’t whether to pursue value-based care, but how quickly they can move from pilots to system-level adoption. Progress will depend on effective change management, stronger data and analytics capability, and cross-sector partnerships, alongside investment in workforce skills and enabling technologies.

Redesign care around integrated pathways, not institutions. Ageing populations, rising multi-morbidity, and workforce shortages are making traditional inpatient models harder to sustain. In Switzerland, for example, demand for hospital services is projected to increase by around 28% by 2045, driven by population growth and ageing alone. But medical and digital innovations are fundamentally changing what can be done outside hospital walls. Advances in surgical techniques, diagnostics, remote monitoring, and digital coordination continue to shorten length of stay and shift activity into outpatient and home-based settings. As a PwC report commissioned by the Belgian Association of Hospital Managers found, ambulatory and same-day surgical pathways supported by digital follow-up reduce hospital stays while maintaining safety. Similarly, transmural cancer pathways using continuous symptom monitoring reduce emergency visits and improve survival. Chronic disease pathways supported by remote monitoring enable earlier intervention and fewer complications.

Going forward, more specialised, complex, and resource-intensive acute and tertiary care should remain centralised, while routine, chronic, and follow-up care should be decentralised where clinically appropriate. The most meaningful progress will come from integrated, indication-based care pathways that combine decentralised delivery with shared accountability for outcomes and costs. This approach will also increase transparency, especially for privately funded systems.

Align incentives to create value-based care. Without aligned incentives, decentralisation risks transferring activity rather than improving outcomes. That’s where value-based care comes in. These models shift the focus to patient-relevant outcomes achieved across the full cycle of care, relative to the costs required to achieve them. This requires measuring outcomes beyond single encounters, including recovery, overall health improvement, and sustainability of those improvements. It also requires looking across organisational boundaries, from prevention and diagnosis through treatment and follow-up. Despite widespread endorsement, fragmented funding, fee-for-service incentives, and inconsistent outcome measurement continue to reward volume rather than value. Across systems, most value-based initiatives remain limited to pilots, individual conditions, or local programmes, rather than being embedded system-wide.

Evolve payment models to enable scale. Fee-for-service can create a challenging dynamic. It rewards activity in specific settings, often penalising providers for reducing admissions or shortening length of stay. Value-based payment approaches such as bundled payments, blended capitation, or outcomes-linked reimbursement offer a better path forward. When designed well, they shift financial risk and reward towards prevention, coordination, and quality while allowing providers flexibility in how they deliver care. To address the challenges of provider resistance and unintended consequences, models require careful design: risk adjustment to avoid patient selection, robust outcome measurement, and transitional support to manage financial volatility during the shift away from volume-based revenue.

The defining longevity challenge of the coming years is not only how long people live, but how well they live. According to a JAMA Network report based on World Health Organization data, healthspan (the years lived free from disease and functional decline) now lags lifespan by 9.6 years globally, and this gap has widened over the past decade. For health systems, focusing on healthspan shifts the objective from treating disease and extending life to preserving function and ensuring a fulfilling life. Longevity strategies therefore focus on delaying the onset of decline and enabling older adults to remain independent and productive members of society. A recent PwC report found that focusing on women’s health, in particular, represents a significant market opportunity and the potential to improve quality of life for half of humanity—whose needs have historically been overlooked in many contexts. This structural transition requires a regulatory and policy environment that actively enables and funds prevention, innovation, and system redesign, while strictly safeguarding safety, quality and scientific rigour.

Embed longevity as a system-level objective. Transitioning from a ‘silver economy’ that manages ageing to an ‘evergreen economy’ that reframes longevity as a growth engine to power productivity and resilience will produce widespread economic gains. The OECD estimates that age-diverse workforces could raise GDP per capita by almost 19% over the next three decades. According to the Centre for Ageing Better UK, setting and achieving a 75% employment target for people aged 50-64 by 2030 in the UK yields economics gains of £9 billion per year. Beyond productivity, older adults represent one of the fastest-growing consumer segments across healthcare, financial services, housing, mobility, technology, and lifelong learning. To realise such benefits, leaders must place greater emphasis on adapting workplaces, workflows, and job design through flexible hours, role redesign, ergonomic adjustments, and lifelong skills development to enable longer, healthier working lives.

Realising such gains depends on a set of systems that influence how people live, move, work, learn, and connect across their lives. Urban design and transport systems determine mobility and social participation in later life. Housing policy shapes whether people can remain safe, independent, and connected as their needs change. Education and lifelong learning contribute to cognitive reserve and adaptability, while labour market structures influence whether longer lives translate into prolonged economic and social contribution or extended dependency. Governments increasingly need to act as system orchestrators, aligning policy and funding across health, social care, housing, transport, employment, and digital infrastructure.

Make ageing in place the default model. Across geographies, older adults consistently prefer to remain in their homes and communities. And home- and community-based care is typically more cost-effective and better suited to chronic disease management. We will see efforts towards operationalising ageing in place at scale, embedding community-based and multi-generational living models rather than pilots. But ageing in place depends on deliberate investment in assistive technologies, caregiver support, rehabilitation, community-based services, and reliable referral pathways. It also involves moving beyond age-segregated housing towards community-embedded and multi-generational models, integrating schools, childcare, shared spaces, and local services. Italy’s Pact for senior citizens illustrates this approach, reframing ageing policy around dignity and independence through stronger home-based, integrated, and community-embedded care.

Improve healthspan through innovation. Advances in digital, assistive, and life sciences technologies are converging to extend healthspan, underpinned by growing consumer demand and investment. Human-centred digital solutions, such as dementia platforms that combine virtual reality, voice interaction, and AI, have demonstrated early evidence of improved cognitive function in ageing populations. Embedding these technologies within existing care pathways, alongside improving digital literacy for seniors and caregivers, will be critical to scaling impact. In parallel, pharmaceutical innovation is targeting shared biological pathways of ageing, with compounds such as metformin, NAD+ precursors, and GLP-1 receptor agonists being tested for broader effects on age-related decline. Together, these evidence-backed, technology-enabled approaches are accelerating a shift towards more preventative, personalised and integrated models of care.

The scope, pace, and power of these trends pose a set of significant challenges to leaders. The to-do list is long, and it requires a shift in mindset. Leaders must move beyond incremental change and embrace holistic transformation, reimagining care models through the lens of prevention, personalisation, and technology-enabled integration. Investing in, and making the most of, the technology and data at our fingertips will enable us to design systems that centre on human experience and solve the problems of people living in the world as it is. Ultimately, healthcare leaders should view this era as a unique opportunity to redefine value and elevate health outcomes globally.

The authors would like to thank PwC’s Global Clinical Advisory Board for their contributions to this report.