Healthcare Is Being Re-Architected
Updated: Aug 12
Healthcare has spent much of the past decade talking about transformation.
2026 looks different.
The pressure to transform is no longer coming primarily from innovation agendas. It is coming from the economics of delivering care.
Margins remain under pressure. Workforces are stretched. Patients increasingly expect healthcare to be accessible outside traditional settings. Data is becoming more valuable and more difficult to govern. Artificial intelligence is advancing faster than most organisations can redesign the workflows around it. Individually, none of these trends is new.
What matters is that they are now converging. Recent research from Deloitte, McKinsey and PwC points toward the same underlying shift: healthcare is moving away from an institution-centred, reactive and labour-intensive model toward one that is increasingly distributed, preventive, data-driven and augmented by intelligent systems.
The transition will not happen evenly and technology alone won't determine the winners.
Executive Summary
1. Economics is becoming the forcing function for transformation
In the US, healthcare-industry EBITDA as a share of national health expenditure declined from 11.2% in 2019 to 8.9% in 2024, according to McKinsey, and is projected to fall slightly further to 8.7% in 2027. Financial pressure is turning productivity from an operational ambition into a strategic requirement.
2. AI is moving toward infrastructure, but deployment remains far behind ambition.
Deloitte found that roughly 30% of surveyed health systems operate generative AI at scale in selected areas, while only 2% have deployed it enterprise-wide. At the same time, 64% of executives surveyed by Deloitte see AI-driven workflow standardisation and automation as a source of cost savings.
3. The geography of care is changing
McKinsey expects continued movement toward ambulatory, home and hospice settings, while Deloitte identifies outpatient expansion, remote monitoring and digital offerings as contributors to future growth. Care is gradually becoming less synonymous with the hospital building.
4. Prevention is moving closer to the commercial centre of healthcare
PwC identifies growing demand for proactive, personalised and continuous health services, while 38% of non-US health-system executives surveyed by Deloitte said their organisations would focus on preventive care and early detection in 2026.
5. Data, trust and interoperability are becoming strategic infrastructure
As healthcare becomes more distributed and AI-dependent, the ability to move trusted data securely across organisations, devices and care environments becomes increasingly important. PwC identifies data liquidity, interoperability, privacy and cyber resilience as central requirements for the emerging model.
Healthcare is beginning to redesign itself around intelligence rather than institutions.
Transformation starts with economics
The most important healthcare technology story of 2026 may not actually be about technology. It may be about margins.
McKinsey estimates that US healthcare-industry EBITDA represented 11.2% of national health expenditure in 2019. By 2024, that figure had fallen to 8.9%, with further pressure expected through 2027. Providers and payers have absorbed much of that deterioration.
That matters because margin is not simply a shareholder issue. Healthcare organisations need financial capacity to expand services, invest in infrastructure, adopt technology, improve patient experience and build new clinical capabilities. When that capacity narrows, productivity becomes strategic.
Deloitte's global outlook reaches a similar conclusion from a different direction. Among 180 C-suite health-system executives surveyed across six developed markets, financial pressures and care-model transformation, workforce and productivity challenges, and cybersecurity emerged as the three forces expected to strongly influence 2026 strategy.
There is optimism: around 70% of surveyed non-US executives expect operating revenue and margins to improve. But their plans for getting there are revealing. Investment priorities include core technology, digital and AI tools, workforce engagement, new outpatient services and new care models. The implication is important. Healthcare is not digitising simply because better technology has arrived.
The economic model is creating pressure to find fundamentally better ways of delivering care.
AI is becoming infrastructure, but healthcare is still learning how to use it
AI occupies a strange position in healthcare in 2026. Its potential is widely accepted. Its enterprise deployment is not.
Deloitte reports that around 30% of surveyed health systems have generative AI operating at scale in selected parts of their organisations. Only 2% report enterprise-wide deployment.
That gap tells us more than another forecast of the healthcare-AI market ever could.
Healthcare does not have an AI-awareness problem.
It has an implementation problem.
Executives appear to understand where the near-term economics may lie.
Deloitte found that 64% of respondents believe AI could reduce costs by standardising and automating workflows. Another 55% see savings potential from predictive analytics applied to workforce optimisation, while 49% expect benefits from technology-enabled patient engagement and remote monitoring.
PwC goes further, arguing that AI is becoming part of healthcare's infrastructure: embedded into how organisations predict needs, prioritise interventions and deliver care rather than added as a separate technological layer. This distinction matters.
The first phase of healthcare AI largely asked:
What can this technology do?
The next phase asks:
What should the organisation look like because this technology exists?
Those are very different questions.
Consider a hospital introducing AI documentation.
If clinicians use the same workflows, managers use the same processes, patients follow the same journeys and the organisation simply inserts an AI tool into one step, the productivity ceiling may remain relatively low. Redesign the workflow itself, documentation, coding, handover, scheduling, follow-up and patient communication and the economics begin to change.
The unit of AI transformation is therefore not the model. It is the workflow.
Healthcare is escaping the hospital
For much of modern healthcare, the institution has defined the experience. Patients travelled to healthcare. Increasingly, healthcare will travel to patients.
McKinsey expects continued movement of care toward lower-cost settings. Ambulatory surgery centres are gaining procedures traditionally performed in hospitals. Home health EBITDA is projected to grow around 6% annually between 2024 and 2029, while hospice EBITDA is estimated to grow approximately 9% annually over the same period.
Deloitte similarly sees outpatient expansion, virtual care, remote monitoring and digital offerings contributing to care-model transformation.
PwC places the trend within an even larger shift toward decentralised and digital-first healthcare, driven partly by consumers taking a more active role in how they access and manage health services.
This changes more than location.
Moving care away from hospitals changes:
cost structures
technology requirements
patient journeys
workforce deployment
reimbursement models
monitoring requirements
competitive boundaries
A patient recovering at home requires a very different operating model from a patient occupying a hospital bed. Remote monitoring, virtual care, interoperable data, logistics, patient engagement and escalation protocols all become more important. And this creates opportunities outside traditional provider organisations. Digital-health companies, home-care providers, diagnostics companies, pharmacies, device manufacturers and consumer-health platforms can increasingly participate in parts of the patient journey that historically belonged almost exclusively to hospitals and physicians.
Prevention is moving from philosophy to business model
Healthcare has discussed prevention for decades. The economics have rarely supported it equally across markets. That may be beginning to change.
PwC identifies a shift in consumer expectations away from healthcare centred purely on treating illness toward proactive services intended to improve both lifespan and quality of life. It also sees healthcare and wellness increasingly blending as digital-first services support more continuous engagement with health.
Deloitte's international findings provide another signal. Among surveyed non-US executives, 45% identified care-model transformation as a leading 2026 trend and 38% said their organisations would focus on prevention and early detection. The contrast with the United States is striking: only 7% of US health-system executives surveyed expected preventive care to be a major organisational trend in 2026. Deloitte links part of that divergence to different reimbursement incentives, particularly the continuing influence of fee-for-service models. This exposes one of healthcare's central strategic tensions. Technology increasingly makes continuous, predictive and preventive health possible. But business models do not always reward it. That gap is likely to become an important battleground. Wearables, diagnostics, remote monitoring, biomarkers, AI-based risk stratification, nutrition, longevity services and consumer health platforms are producing an expanding layer of information before a patient becomes acutely ill. The organisations capable of translating that information into interventions and finding sustainable ways to get paid for doing so could capture an increasingly important part of healthcare's value chain.
Data becomes the connective tissue
A distributed healthcare system creates a fundamental problem. The patient may be at home. The clinician may be in a hospital. A wearable may collect one stream of data. A diagnostic provider holds another. The EHR contains another. An AI system needs access to several. An insurer may need evidence of the resulting outcome.
Without information moving between those environments, decentralisation creates fragmentation rather than transformation.
PwC consequently identifies data liquidity: the secure, interoperable and increasingly real-time movement of health information, as a critical priority, while simultaneously emphasising privacy and cyber resilience.
Deloitte's findings reinforce the risk side of that equation: cybersecurity ranks among the three major forces shaping health-system strategies in 2026.
This means interoperability should no longer be viewed primarily as an IT problem. It is becoming a business-model problem. AI needs data. Remote care needs data. Personalisation needs data. Preventive healthcare needs longitudinal data. Value-based models need outcomes data.
Patients increasingly expect information to follow them across the healthcare journey.
The more intelligent and distributed healthcare becomes, the more valuable trusted information exchange becomes.
A New Healthcare Operating Model
These five shifts should not be viewed in isolation. Their strategic significance lies in how they reinforce one another and, together, begin to reshape the underlying economics and architecture of healthcare delivery.
Financial pressure is increasing the need for productivity at precisely the moment workforce constraints are making traditional approaches to capacity expansion more difficult. This creates a stronger economic case for automation and augmentation. Advances in AI, in turn, expand what can be automated, predicted and supported by technology, but their effectiveness depends heavily on the quality, accessibility and interoperability of healthcare data.
The same dynamic is unfolding beyond the walls of the hospital. Remote monitoring and connected technologies are making it possible to generate continuous health data outside traditional clinical settings. Continuous information can enable earlier identification of risk; earlier identification creates opportunities for intervention before conditions escalate; and earlier intervention strengthens the economic and clinical case for shifting healthcare from episodic treatment toward prevention and continuous management.
Consumer expectations add another force to this transition. Patients increasingly expect greater convenience, accessibility and involvement in their healthcare, accelerating the movement of appropriate services toward outpatient, virtual and home-based environments. But decentralising care is not simply a matter of moving an existing service from one location to another. It requires different technology infrastructure, workforce models, data flows, clinical protocols and, in many cases, different economics.
Taken together, these forces point toward what Bolgarz defines as the Healthcare Operating Model Shift: a gradual transition from an institution-centred, reactive and episodic system toward one that is increasingly patient-centred, preventive and continuous; from labour-intensive delivery toward technology-augmented care; from fragmented information toward interoperable data; from predominantly human-only workflows toward collaboration between people and intelligent systems; and, ultimately, from models that reward activity and volume toward those that place greater emphasis on outcomes and value.
The important word is toward. This is a direction of travel, not an overnight transition.
Healthcare will not suddenly arrive at this operating model in 2027. Legacy infrastructure, fragmented data, reimbursement structures, regulatory requirements, clinical risk and organisational resistance will continue to constrain the pace of change. The transition will also vary considerably between markets, healthcare systems and areas of care. Some elements may advance rapidly while others remain structurally difficult to change.
What is becoming harder to ignore, however, is the direction in which these forces collectively point. The strategic challenge for healthcare leaders is therefore not to predict exactly when the new model will arrive, but to understand which parts of their organisations need to begin changing before it does.
The Strategic Implications
For healthcare executives, the implications extend well beyond technology investment. They require decisions about how organisations operate, where they compete and where they will create value as healthcare becomes more distributed, data-driven and technology-augmented.
1. Redesign before digitising
Technology should not become a more efficient way of preserving an inefficient process. Yet this remains one of the risks of healthcare digitalisation: organisations introduce new tools while leaving the underlying workflow largely unchanged.
The stronger approach begins with the operating model. Leaders should first determine how a process would ideally work if existing technological and organisational constraints were removed. Only then should they decide where AI, automation and other digital capabilities can eliminate friction, augment human expertise or remove work entirely.
This distinction will become increasingly important as AI capabilities mature. The greatest productivity gains are unlikely to come from inserting AI into every existing workflow. They are more likely to come from identifying workflows that no longer need to exist in their current form.
2. Follow the patient journey, not the institution
As care becomes more distributed, some of the most attractive growth opportunities may emerge between the traditional boundaries of healthcare: between hospital and home, diagnosis and continuous monitoring, treatment and prevention, and clinical healthcare and consumer health.
For healthcare organisations, this requires looking beyond existing service lines and examining the complete patient journey. Where does information disappear? Where does engagement stop? Where are patients unnecessarily moved into higher-cost settings? Where could continuous monitoring replace episodic assessment? Where can intervention occur earlier?
These transition points are not merely operational gaps. They can become new markets.
Organisations that understand how value moves across the patient journey will be better positioned to identify emerging categories before those categories become established parts of the healthcare system.
3. Treat workforce strategy and AI strategy as the same conversation
AI strategy is frequently treated as a technology agenda. In healthcare, it is increasingly a workforce agenda as well.
If AI changes how administrative, operational and clinical work is performed, organisations cannot determine their technology strategy independently of their workforce strategy. Leaders will need to distinguish between activities that can be automated, those where AI can augment human capability, and those where clinical judgement, empathy, accountability or complex decision-making should remain fundamentally human.
The objective should not simply be labour substitution. In a sector facing persistent capacity constraints, one of AI's more important contributions may be allowing scarce human expertise to be concentrated where it creates the greatest value.
The organisations that manage this transition successfully will therefore need more than technology adoption. They will need workflow redesign, new capabilities, effective change management and clarity around the evolving relationship between human and machine decision-making.
4. Build the data foundation before pursuing sophisticated AI
The sophistication of an AI system matters little if the information supporting it is incomplete, inaccessible or unreliable.
As healthcare becomes more connected, distributed and intelligent, interoperability, governance, cybersecurity and data quality move from technical considerations to strategic capabilities. AI requires data. Remote care requires data. Personalisation requires data. Prevention increasingly depends on longitudinal data. Outcome-based models require organisations to understand what happened to patients across the entire care journey.
This makes foundational infrastructure considerably more important than its visibility might suggest.
For many healthcare organisations, the highest-return AI investment may therefore begin with something that does not look like AI at all: creating the architecture that allows trusted information to move securely to the people and systems that need it.
The less glamorous infrastructure may ultimately determine the return generated by the more glamorous technology.
5. Reconsider where the organisation creates value
The deepest strategic implication is not technological. It concerns the future distribution of value across healthcare.
If more care moves outside hospitals, if prevention captures a greater share of healthcare expenditure, if AI absorbs portions of administrative work, if continuous monitoring reduces dependence on episodic interactions, and if consumers become more active participants in managing their health, then the relative value of different capabilities across the healthcare system will change.
Some activities that are strategically important today may become commoditised. Others that currently sit at the edges of healthcare data orchestration, remote monitoring, patient engagement, predictive intervention and the connection between consumer behaviour and clinical care could move closer to its economic centre.
Every healthcare organisation should therefore be asking a deceptively simple question:
If healthcare becomes more preventive, distributed, intelligent and consumer-directed, which parts of our current business become more valuable and which become less?
The organisations that answer that question early can position themselves for the transition. Those that wait until the economics have already shifted may find themselves adapting to a healthcare system that others have helped design.
Sources
Deloitte — 2026 Global Health Care OutlookSurvey of 180 C-suite executives across Australia, Canada, Germany, the Netherlands, the United Kingdom and the United States.Read the Deloitte report
McKinsey & Company — What to Expect in US Healthcare in 2026 and BeyondAnalysis of healthcare economics and segment-level outlooks across payers, providers, healthcare services and technology.Read the McKinsey analysis
PwC — Global Health Report: Consumers and Powerful Advances in AI Are Transforming HealthcareAnalysis of five structural trends affecting global healthcare, including AI, data, consumerisation and changing care models.Read the PwC Global Health Report
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