Key Insights
- Innovating with AI presents the opportunity to simultaneously enhance access, affordability, experience, and quality of care.
- Payers can transform from transaction processors to enablers of personalized, efficient care.
- A tenfold higher access to high-quality primary care is possible.
- Consumer-focused and outcomes-based models can expand access to breakthrough therapies.
- Health services and technology companies can accelerate value by transforming critical workflows with AI.
- Health systems can see higher productivity and asset utilization.
- The challenge is in navigating the exponential speed of AI advancement, the linear speed of core technology modernization, and the uneven speed of organizational change.
More than 500 million years ago, temperatures rose by up to 6 degrees Celsius, making Earth inhospitable to many forms of life. Still, leaps in genetic developments occurred and oxygen levels doubled. This Cambrian period of Earth’s history saw an accelerated evolution of the most disparate life forms ever in our planet’s history. All species today descended from life forms that originated in this explosion.1
The healthcare industry2 stands at a similar evolutionary inflection point. The industry is well into its sixth year of a harsh operating environment—costs are rising and reimbursement is falling. All indicators suggest the temperature will stay elevated for the foreseeable future.
At the same time, the AI and biopharma revolutions are providing once-in-a-generation breakthroughs. Healthcare consumers, clinicians, and industry stakeholders are rapidly adopting AI, with more than 40 percent of physicians using OpenEvidence daily3 (Exhibit 1). And drug development is accelerating.4 Advances in life-saving treatments, such as those for metabolic disorders, are redefining chronic condition management,5 while programmable medicine through cell, gene, and mRNA platforms, as well as AI-enabled personalized diagnoses and treatments, are scaling rapidly. McKinsey Global Institute research shows that emerging technology arenas (such as AI, robotics, and bio-frontiers) are capturing a majority of value creation across industries, and healthcare should be no exception.
The US healthcare industry, physicians, and consumers are steadily adopting AI.
1OpenEvidence combines AI-powered ambient listening with insights from the latest clinical literature.
Additionally, healthcare is among the top three destinations for private capital, with an estimated $330 billion to $440 billion available to deploy.6 The industry is also a top destination for mission-oriented talent. Together, capital and talent serve as the oxygen needed for healthcare organizations to survive, scale, and diversify.
So, are we on the cusp of an explosion of healthcare innovation that will spawn great new business models that define success for the future? It’s important to acknowledge that change in healthcare is tough—appropriately so given that people’s lives are at stake. The healthcare industry employs more than 20 million people, and innovation will require most of them to do their jobs differently and learn new skills. Concerns about AI-driven job loss abound, but demand for healthcare services is rising and access remains inadequate. Therefore, we expect healthcare employment is poised to grow rather than contract. Managing this transition requires care. Clinical safeguards and regulations are essential to ensuring the safety of new treatments and the use of AI. Equally important is the ability of healthcare organizations to implement change while continuing to deliver safe, reliable, and uninterrupted care.
In this article, we offer five provocations for practical avenues toward a diverse set of business models. This is not meant to be a comprehensive list of all potential innovations, but rather a source of inspiration for leaders.
Reimagine the healthcare payer
Healthcare payers create networks, define and enforce rules, set prices, and process payments. AI can do many of the tasks embedded in those functions, or prompt their complete reorganization or even obviation. The impact will look different across three categories of payer work: transaction-oriented work, knowledge-oriented work, and relationship or management work.
Start with transaction-oriented work. At a typical payer, 65 to 80 percent of jobs are transaction oriented, such as claims processing; AI could fully automate all or almost all of these jobs, based on our analysis.7
The bigger question is: Do we need claims at all in a world where universal electronic medical records exist and AI can review that data? Medical records are a far closer representation of patient needs and services rendered than a claim, which is ultimately a billing artifact derived from clinical documentation. AI agents could efficiently analyze the appropriateness of treatment and diagnosis coding, as well as assess clinician performance, safety, quality, and more by evaluating longitudinal medical records against medical policies, reimbursement policies, and health insurance benefits and then make accurate payments.
In such a world, a payer is still necessary—not merely as a claims processor but as the platform that integrates data with intelligence to enable better health and care delivery. A good analogy comes from modern-day stock exchanges, which have gone beyond simply completing trades. Stock exchanges create indexes that can be used to develop investment products and provide a variety of security solutions to enable asset managers and traders to operate more effectively. Such a business model for payers would derive its value from pushing down transaction costs to a de minimis level and generating revenue from new data-driven, value-added products and services to enable better health and improved care delivery.
Next, consider knowledge-oriented work. Another 10 to 25 percent of jobs at a payer are knowledge oriented, such as pricing actuaries and medical management nurses.8 AI could deliver, in our estimation, as much as 50 percent greater efficiency in these jobs by handling tasks such as looking up information, cleaning and collating data, and taking notes. More important, these knowledge-oriented jobs, reimagined, could massively improve healthcare by helping payers live up to their role as orchestrators of the healthcare system.
The freed-up capacity of knowledge workers could open the next vectors of innovation, some of which would admittedly require regulatory changes:
- The disaggregation and reallocation of medical risk to create risk-aligned funding models and sophisticated payment models.9 For example, in cancer care, a payer could carve out cancer risk from an employer-sponsored plan and create a shared-risk model across the value chain: payers for population and severity risk, the oncologist for treatment pathway selection risk, related clinicians for whole-person care and complications risk, the health system for procedural risk, and the pharmaceutical company for therapeutic safety and efficacy risk. Similarly, for patients with chronic diseases, a payer could create a risk-impaired annuity model—one in which funding is calibrated to the patient’s chronic-condition risk and spread over time—with outcome risk shared across patients (for example, lifestyle behavior and treatment adherence), primary care physicians and the broader care team, relevant specialists, the pharma company, and the payer.
- The enablement of “n of 1” healthcare delivery. Payers are uniquely placed to create a full view of the consumer. The opportunity is to extend beyond formal medical care to having a fuller view of each consumer by becoming the engagement platform through which they take care of their health. This would go far beyond medical care alone and encompass fitness, sleep, nutrition, mental health, spiritual health, and more. Through such an engagement platform, consumers could access a variety of health and well-being solutions, access formal medical care when needed, and connect with appropriate clinicians and treatments, confident that they are achieving the best possible care. The platform would need consent, privacy and data governance, and boundaries on data use.
Finally, the remaining jobs at a payer, including sales, are relationship oriented or related to management. AI could also improve the efficiency of individuals in these roles by up to 50 percent, in our estimation.
Taken together, AI has the potential to reshape the payer workforce and enhance the focus on value-added activities that improve care and experience.
These ideas are not new, but they can be implemented now. AI absorbs the complexity and lowers the cost of intelligently personalizing healthcare for each individual, allowing such models to flourish.
Empower consumers through an always-on care model
In this century, while the average American’s lifespan has increased by two years, their health span (years lived in good health) has increased by only eight months.10 Improving health span requires clinicians to enable preventive care and individuals to actively manage their health in daily life. However, the current model of primary care cannot deliver that level of support given the shortage of primary care physicians (PCPs).
The conditions are now in place to provide continuous access to high-quality primary care to all individuals on demand with an AI-enhanced direct primary care (DPC) model.
AI can transform DPC, a membership fee-based model, to deliver scalable and financially accessible primary care. Because DPC physicians are not paid per visit, AI-enabled productivity gains are economically attractive rather than being seen as a reduction in visits and therefore revenue. Roughly 60 percent of primary care visits involve chronic disease management and preventive care.11 Such care is protocol driven, involving evidence-based pathways that AI agents can largely execute with the physician’s overall guidance. A DPC physician augmented by clinical AI could potentially serve more than 3,000 patients, according to our research,12 rather than today’s average of about 400,13 while delivering more continuous and personalized attention than traditional primary care provides.
Utah’s 2026 Doctronic pilot has extended this logic to prescribing, demonstrating that AI could autonomously renew 192 commonly prescribed chronic medications and had a 99.2 percent match rate to physician decisions.14 An important barrier—patients’ ability to pay with tax-advantaged dollars—has now been addressed by H.R. 1,15 which allows the more than 59 million Americans covered by health savings accounts (HSAs) to use those pre-tax dollars to fund DPC membership fees. A DPC membership combined with an HSA-eligible high-deductible health plan has the potential to provide superior access to continuous care compared to today’s model.
Such a model can also be enhanced with a variety of additions, such as personalized agents for health improvement assistance, access to health improvement solutions, direct-to-consumer (DTC) diagnostics, and DTC pharmacy services.
Rethink acute care delivery
The healthcare delivery system’s inability to improve productivity is legendary, as is the fact that waves of technology have added to, rather than reduced, costs. The productivity growth gap between healthcare delivery and the overall US economy from 2019 to 2025 was about three percentage points,16 a gap large enough that closing it would double the standard of living from one generation to the next, in our estimation.
The signal to rethink acute care is clear: Medicare dominates volume growth and reimbursement continues to be pressured, site neutral payment lurks, and legislative proposals like Medicare for All would tip the scales further. Profitability at Medicare rates is imperative. In our experience, clinical-care organizations have achieved meaningful transformation in the past few years but not enough.
Perhaps the best analog for such a business-model rethink comes from the airline industry, which, like healthcare, has substantial fixed capital assets and a large specialized workforce. In the face of relentless price pressure after deregulation, the airline industry reduced cost per passenger mile by half.
Halving costs in US acute care would be a game changer. Of course, the shift to more efficient sites of care has been a positive trend for many years and continues with meaningful growth in ambulatory settings. But more will be necessary. For instance, a multifold increase in hospital capital asset utilization is important. On average, the hospital capital cycle is 30 to 40 years long, in our experience. Over the next 30 years, we anticipate that acute procedure demand might decline in many geographies due to demographics and the impact of new therapies such as glucagon-like peptide-1 (GLP-1) receptor agonists.17 Markets vary meaningfully along three important dimensions: the size of the over-65 population is a major driver of current demand; the ratio of working-age adults to seniors is an indicator of growth in demand over the long run; and capacity utilization is an indicator of whether existing infrastructure can absorb future demand (Exhibit 2).
Variations in US healthcare markets suggest value from strategic diversity.
1Calculated as weighted average of bed occupancy by city: total days/(total beds × 365).
Growth markets with constrained capacity are good candidates for investment—but deploying capital toward ambulatory sites with a higher growth outlook and ROIC should be the focus.
In growth-constrained markets, particularly where capacity is also constrained, clinical-care organizations should redouble their focus on length-of-stay improvements to free up capacity. More important, they must innovate to increase utilization of current fixed assets rather than building new capacity. The airline industry substantially reduced the cost per passenger seat mile by increasing the amount of time planes are flying—an example hospitals would do well to replicate. For example, if an operating room was utilized like major US airlines utilize their aircraft, we estimate that it would see 2.5 times its current weekly utilization.
Unlock affordable access to the biopharma revolution
The pharmacy dispensing, management, and services value pools continue to grow, spurred by the biopharma revolution. At the same time, the economic model is entering a period of material upheaval due to multiple regulatory changes. The competing objectives—providing access to amazing possibilities for extending healthy life or ensuring the affordability of treatments—scream out for the need for innovation.
A few potential models exist based on two dimensions: whether they align with the secular growth of new treatments and whether they are zero-sum or focused on positive value creation. Where innovation is needed—and can thrive—is in models that ensure access to new treatments while triggering positive value creation. Consider a few avenues that could be combined in various permutations to form creative models:
- Consumer empowerment. Many aspects of health management are more directly in the hands of the individual than the healthcare ecosystem. For example, addressing obesity and several chronic conditions requires individuals to make lifestyle and behavioral modifications. Individuals, however, also require assistance in achieving these goals including access to medications like GLP-1s and those targeting the glucose-dependent insulinotropic polypeptide.
- For individuals trying to address obesity, consumer-direct models could be most effective. Such models could combine direct-pay access to medications combined with wearables and other over-the-counter devices (for instance, glucometers) for tracking and fitness, and nutrition coaches to build muscle mass. These services could enhance direct models for dispensing medications, which are seeing major growth already (for example, the share of Zepbound prescriptions initiated through LillyDirect jumped from 25 percent in the first quarter of 2025 to 55 percent in the second quarter of 202618). When such an offering is covered through health insurance (subject to deductible), insurers could create consumer wellness incentives.
- For individuals with chronic conditions, a more intense version of the combination described above that involves PCP coordination and clinical intervention could be appropriate. In addition to wellness incentives, a risk-based model with incentives aligned to outcomes for the pharma company, PCP, and payer would help ensure value creation for all stakeholders while enhancing patient affordability and outcomes.
- Funding models for high-cost treatments. Cell and gene therapies and other expensive treatments—such as for cancer—might benefit from payment models that spread out payments for treatments and tie them to outcomes. For instance, a center of excellence delivery model that includes the oncologist, the necessary additional clinicians (mental health counselors, nutritionists, and so on), and the pharma company would share risk for patient treatment and ensure the appropriate choice of targeted treatments and whole-patient care. In addition, the payer could create a risk-based carve-out for an employer plan to provide greater certainty in cash flow planning for employer sponsors of health benefits. Such carve-out programs could be further enabled by reinsurance or securities contracts that hedge the cost of treatments against pharma company revenues or equity values.
Develop an AI-centric business model for the healthcare services and technology sector
The healthcare services and technology (HST) sector has been the fastest growing and most resilient profit pool for several years. Behind this growth, however, hides a continual cycle of obsolescence at one end and new business model creation at the other end. And AI is accelerating this creative destruction. When considering whether and how to reinvent the business model, leaders should consider opportunities along two axes: first, the level of value added by AI in the solutions offered, and second, how central the solution is to the customer’s value creation or operational workflow (Exhibit 3).
The fragmented healthcare services and technology sector faces business model reinvention choices.
Generating a measurable benefit either by reducing total cost of care or improving operating efficiency will be table stakes, as payer and health system customers’ internal capabilities are improving rapidly because of AI. Successful business models will lean more heavily into technology and be less dependent on services-centric strategies. In addition, the moat for HST businesses lies in being deeply integrated into clinician workflows, patient interactions, and the care encounter. This can be achieved either through high-adoption, mission-critical solutions or by providing the enabling platforms on which other solutions depend. Individual businesses can adopt specific strategies for success, though. Examples include using AI to disrupt traditional workflows that are often services-centric (for instance, revenue cycle management) or integrating AI solutions into proprietary and interconnected data (for example, to connect patient-level clinical information with broader claims, population health, and patient engagement information).
Master innovation in a three-speed world
The opportunity for leaders to improve healthcare has perhaps never been greater. A failure to innovate could prompt a further decline in public trust in the healthcare system and intensify calls for major government action. The latter would only exacerbate the downward economic trajectory that the healthcare industry has experienced since the COVID-19 pandemic. Clearly, the required future models will not naturally emerge; healthcare leaders will need to actively incite, motivate, and nurture them.
So how must leaders move forward? While we do not provide a full playbook in this article, we urge leaders to focus on speed, specifically the speed to value, as the primary source of advantage. In today’s world, this requires mastering the art of managing across three speeds—the exponential trajectory of AI, the linear progression of modernizing the core technology infrastructure, and the sublinear trajectory of organizational change.
AI capabilities are improving at an exponential pace. In such an environment, healthcare leaders need to move beyond the AI hype. Equally important is not falling behind. Leaders need to have a clear window into AI’s progress and where it is gaining traction. They will need to forge connections not just with AI innovators but also with leaders in industries that may be further ahead in adoption than healthcare. New entrants in healthcare are still stymied by complexity and regulations, preserving the competitive moat for the industry, but the AI era does raise the possibility of disintermediation by industry-adjacent participants or new entrants. Healthcare leaders therefore should be continually scanning the landscape, identifying emerging models, and creating approaches for partnering—and exiting partnerships—with entrants.
AI may be improving exponentially, but changes to legacy technology infrastructures are slower, moving in a linear way. To account for this mismatch, healthcare leaders will need to accept the constraints for their core systems while simultaneously reducing the centrality of those systems to value creation. It will be critical for them to create a semantic layer within their technology infrastructure that delinks development of new products, services, solutions, and capabilities from core systems. In this way, they can maintain speed to market without replacing entire systems.
Perhaps the biggest constraint to unlocking value from AI is the nature and speed of change itself: As every leader knows, organizational change is hard, and a majority of change efforts fail to reach their objectives, in our experience. Worse yet, organizations also demonstrate recidivism in their change efforts. To improve the odds of success, CEOs and senior leaders must lead from the front. Perhaps most critical to change in healthcare is articulating the reasons for change and elucidating the value for all stakeholders, including patients, consumers, employees, and communities.
Innovation is not limited to new products; it includes the ability to conceive, develop, deliver, and scale new services, processes, and business models that create net new growth. That broader definition matters here: Healthcare leaders will need to make innovation an operating discipline embedded across all parts of the organization, not an episodic initiative or an isolated department.
Healthcare is a purpose-driven industry. This Cambrian moment provides the opportunity to bring the industry closer to the aspiration of providing what every individual deserves: access to high-quality care, delivered safely, with a great experience, and at an affordable price. The original Cambrian explosion unfolded over millions of years; healthcare leaders do not have that luxury. The organizations that evolve fastest—reshaping clinical models, business models, and operating models together—will define the next era of healthcare.
