What pharma can learn about AI adoption from Brazil, India and China

ZS’s 2025 Future of Health Report found healthcare consumers in the seven countries we surveyed were united in their desire for more convenient and personalized healthcare experiences. And by and large, consumers across the U.S., Brazil, U.K., Germany, India, China and Japan say they’re ready for data, AI and technology to play a larger role in healthcare. On the other side of the exam room, healthcare practitioners (HCPs) are increasingly open to integrating AI into clinical workflows.

While the openness to clinical AI is global, it’s unevenly distributed. Consumers and providers in Brazil, India and China stand out as especially receptive—by a pretty wide margin. To unpack what’s behind this readiness—and explore how pharma companies can translate it into meaningful value for patients, providers and their own business—we brought together ZS leaders with on-the-ground experience across these high-growth markets.

Bill Coyle: We’re seeing much greater openness to AI among consumers and providers in Brazil, India and China than in the U.S. or Europe. Bas, what do you think is behind that in China?

Bas Ludoph: In China, people are already widely using digital services and AI outside of healthcare, so there’s a general comfort level among the population. Unlike in Europe and the U.S., where AI may be seen as more of a threat to entrenched healthcare stakeholders, both providers and patients are generally receptive to it in China. Many healthcare providers (HCPs) in China have very high patient loads, and aging is increasing demands on the healthcare system. The Chinese government also has made AI in healthcare a strategic priority—that means both supporting the development of AI solutions as well as their adoption. Many of these AI solutions ease physician burden and improve care quality.

BC: Priyanka, Sarah—are you seeing the same pattern in India?

Priyanka Paul: India has more than 500 million smartphone users, which supports faster uptake of digital tools, including AI. It’s also a country where 65% of the population lives in rural areas, while 75% of HCPs live in cities. India leads the world in mobile data consumption per subscriber and offers one of the world's cheapest data rates. So, I think people see AI as a way to bridge the gap between supply and demand.

Sarah Jegasothy: It’s also true that the healthcare system in India can be challenging to navigate, so people see an opportunity for AI to play the role of “neutral adjudicator”—to give healthcare consumers confidence they’re being given the right treatment approach.

BC: Anne, what’s fueling that openness in Brazil?

Anne Agopyan: Although much improved, Brazil has a significant shortage of physicians. Doctors are overworked, which makes people receptive to anything that can help—and that includes AI. On top of this, many private medical universities in Brazil don’t have a teaching hospital, so many doctors enter the workforce without completing a residency program. AI can be used to make doctors more efficient but also to help less experienced doctors be more effective.

BC: In the U.S. and Europe, doctors seem more comfortable using AI for administrative tasks than for direct care. But in China, Brazil and India, that gap is a lot smaller. Why do you think this is—and what should pharma take from it when thinking about partnerships?

PP: In India, there’s momentum and readiness on both the supply and demand sides. Not only do we see hospitals using AI to automate routine tasks, like scheduling and clinical documentation, but we also see them deploying clinical intelligence engines for primary care and even chronic conditions.

SJ: Pharma can play a significant role in diagnostics—helping ensure the right patients are identified and guided through the system with a focus on cost-effectiveness.

BL: About 70% of hospitals in China have adopted digital recordkeeping systems, which provide a rich source of structured and unstructured data for AI applications. As a result, there are many players—ranging from big tech and AI startups to universities—working on AI diagnostics and treatment solutions. These solutions might provide near-real-time diagnosis or triage recommendations based on patient history, lab data and updated clinical guidelines. Others may help pathologists screen out negative samples or recommend when a heart-transplant patient is ready to be removed from an ECMO machine. These solutions can help boost quality of care and help hospitals achieve key metrics.

It’s also true that, in China, patients don’t always have a strong relationship with their prescribing physician. This is driving interest in AI tools that can extend the duration of therapy by using AI to detect signals a patient is at risk of dropping off and then suggesting interventions to keep them adherent.

The opportunity for pharma is to find the key leakage points in a treatment journey and then collaborate to address them. Multinational pharma companies in China have collaborated with local companies to develop AI tools that help pathologists interpret PD-L1 levels in lung cancer tissue samples, detect COPD from cough sounds and power clinical decision support systems that flag potential rare disease patients.

AA: In Brazil, we’re seeing growing traction as labs and hospitals turn to AI to reduce costs in patient care and diagnosis. That said, adoption still appears to lag countries like China and India.

BC: Zooming out a bit, where do you see the biggest opportunities for AI to move the needle at the health system level in these countries?

BL: Given China’s vast population, uneven distribution of medical resources and aging demographics, AI will play different roles across market segments. In more developed cities, the focus may be on supporting complex medical decisions, improving efficiency and managing heavy workloads. In less developed areas, AI’s greatest value may lie in enhancing clinical capabilities—especially by aiding diagnosis and treatment of less common conditions.

PP: India’s public health infrastructure is highly fragmented, with inefficiencies in record management, care coordination and scheduling. AI can play a powerful role in improving systemwide efficiency. It also holds promise for delivering more patient-led care through self-serve tools, virtual health navigation, AI chatbots and similar solutions.

SJ: India is a large, fragmented market, so AI offers the potential to scale solutions in ways that were previously unthinkable. The problem is the stakeholder pathways are less defined than they are in the U.S. or western Europe—so you can think big, but how do you shrink it to that first actionable step?

BC: And in Brazil?

AA: Beyond easing physician workload, AI is also seen as a way to help bridge gaps in medical education—especially given the shortage of specialists compared to general practitioners.

BC: You’ve already flagged a few barriers to getting these kinds of solutions to market. What else should we be watching for?

PP: Regulatory clarity and validation pathways for AI in clinical care remain limited. While the Digital Personal Data Protection Act provides a framework for personal data use, it’s still in its early stages. On top of that, the reimbursement data infrastructure is highly fragmented, with unstructured data scattered across disconnected layers of the healthcare system.

BL: In China, key barriers to AI adoption include limited data sharing across hospitals and the lack of standardized inputs for unstructured patient records—both of which undermine data quality. The regulatory framework for AI-driven medical devices is also still evolving, creating ambiguity, risk aversion and delays in product approvals. Reimbursement pathways remain unclear.

Adoption challenges extend beyond regulation. If doctors must be persuaded to prescribe or recommend an AI solution, that typically requires a sales force—an expensive investment that raises a fundamental question: What’s the incentive for a doctor to adopt an AI tool? On the patient side, willingness to pay is low, especially for direct-to-consumer apps, as many Chinese users have been conditioned to expect digital health tools to be free.

BC: And in Brazil?

AA: Data sharing will be one of the biggest challenges. The government is relatively open to sharing—so long as it retains control—which often introduces bureaucratic bottlenecks. In the private sector, data is seen as a competitive asset, so there’s little incentive to share it.

BC: For patient- or consumer-facing tools, you mentioned cost as a hurdle. So, what do you see actually driving adoption?

BL: The end-customer benefit must be clear. For patients in less developed areas in China, that might be access to better care without having to travel to a larger hospital. For other patients, it might be access to physician follow-ups or receiving data about their health condition. Solutions designed for older adults often will require nurses to sign up patients and family member support to drive adherence.

BC: And for physicians, how would these tools need to plug into systems they’re already using to get traction?

BL: Doctors in China are extremely busy, so they’re open to tools that save time. The country already offers many examples of AI solutions that streamline clinical workflows, automate administrative tasks, optimize resource allocation and reduce wait times.

Patient-physician interactions in China are often brief and transactional. That makes tools that capture patient information—and then surface it to HCPs at return visits or help ensure patients come back—particularly valuable. And of course, solutions that reduce clinical risk and improve care quality, such as AI-powered clinical decision support systems, are also gaining traction with providers.

BC: Priyanka, Sarah—what do you see as the main adoption pathways, both for consumers and for providers in India?

PP: Adoption is far more likely when AI tools are embedded into platforms patients and doctors already use—like WhatsApp or employee health benefits programs. There’s no co-pay model to support mass adoption, though NGOs and government initiatives are helping drive uptake in rural areas. Neither public nor private insurers reimburse for AI services, so hospital deployment often requires flexible, open pricing models and evidence-backed pilots that demonstrate clear benefits in convenience, efficiency or patient outcomes.

SJ: Apollo Hospitals is a strong example of AI being implemented with a clear financial incentive—to drive operational efficiencies.

BC: Priyanka, you mentioned evidence-backed pilots. Is the idea that providers get to test AI tools—maybe even with some funding—to build confidence before making a full commitment?

PP: That’s exactly right. The AI solution developer, either a pharma company or technology provider, would be the sponsor.

BC: Anne, how do you see AI adoption playing out in Brazil? What are the real pathways?

AA: In Brazil’s public sector, adoption will largely be driven by public administration, with physicians having limited influence—so progress may be slower. That said, the public system is where inefficiencies are most pronounced, making it the area with the greatest potential for AI to create meaningful impact. Notably, more people in Brazil own mobile phones than refrigerators, so AI tools accessible via smartphones are likely to see smoother adoption—both among patients and providers.

BC: Fast forward five or eight years—where do you think AI will make the biggest difference?

PP: Access to care. In such a fragmented healthcare system, improving access to care is critical—and this is where most government initiatives in India are currently focused. Additionally, extending specialist-grade care and diagnostic services to remote locations, along with efforts to reduce medical errors, would have a significant impact.

BC: And you, Bas? What about in China?

BL: I expect China to lead the world in using AI to transform both everyday healthcare delivery and cutting-edge medical innovation. It has the technical capabilities, a robust tech ecosystem, open-minded clinicians and patients, and strong government support—all the ingredients needed to scale AI in healthcare.

BC: And in Brazil?

AA: The healthcare system here is at a tipping point. Private insurers are operating in the red, with some collapsing entirely. In the public system, wait times for exams are growing and specialist shortages are worsening. We’re training doctors and building hospitals—but there’s a widening gap between the infrastructure we have and how effectively we use it to deliver better care. AI isn’t a silver bullet, but it can be a critical part of the solution.

BC: What advice would you give to a pharma GM in Brazil—or someone at global HQ—who’s trying to get started here?

AA: Big pharma companies need to demonstrate they’re in Brazil for the long haul—not just to get their next drug reimbursed. Even well-meaning solutions, like those aimed at increasing exam volumes, can be met with skepticism. They’re often seen as thinly veiled efforts to diagnose more patients and sell more drugs. To build trust, pharma must approach engagement almost like philanthropy: Start by helping solve systemic problems that benefit the broader health system, not just the bottom line.

From afar, Brazil’s healthcare challenges might resemble those of developed countries. But that’s an illusion. We’re aging before we’re affluent, facing the same pressures as high-income nations—like rising cancer rates—without the financial means to manage them effectively. Our challenges run deeper and are more structural than those in the U.S. or Europe.

BC: And Bas—same question, but for China?

BL: Finding the right partner is critical in such a fast-moving market. A deep understanding of the regulatory and data privacy landscape is also essential. But ultimately, success depends on choosing an area aligned with the public interest—because gaining stakeholder support requires more than just building AI for AI’s sake.

It’s also important to recognize that scaling digital health initiatives is costly, with much of the investment required upfront. That makes driving adoption and sustained use not just important, but essential to realizing impact.

BC: And what about India?

PP: First, it’s about identifying the right partners to implement solutions that address the most pressing healthcare challenges. Then, it’s ensuring regulatory and ethical compliance to sustain the trust of both healthcare professionals and patients.

SJ: Have a bold vision but start with a focused initiative where you can deliver impact quickly. Then, identify who within your organization has the skills, capabilities and relationships to turn that vision into reality. The devil is in the details.