Earning Trust for AI in Health: A Collaborative Path Forward
Health care systems globally face growing pressures: rising costs, workforce shortages, and persistent inefficiencies. In this context, AI offers transformative opportunities to enhance patient outcomes and optimize system performance. But realizing AI’s benefits in health care requires responsible development, rigorous evaluation, and a deliberate focus on building trust among stakeholders.
Today’s regulatory frameworks, designed primarily for pharmaceuticals and medical devices, are not fully suited to manage the probabilistic, dynamic nature of AI technologies. Traditional evaluation methods, which emphasize pre-market validation, struggle to accommodate AI systems that evolve post-deployment. As AI adoption accelerates, regulatory models must evolve accordingly.
New research from the World Economic Forum and BCG identifies three urgent priorities to earn trust for AI in health:
Address fragmentation and build technical capacity. Current AI ecosystems are fragmented, and many health leaders lack a deep understanding of AI technologies. Health systems must build technical literacy among decision makers so that they can critically assess and responsibly integrate AI solutions.
Adapt evaluation and regulatory frameworks. New approaches, such as regulatory sandboxes, post-market surveillance, and life-cycle monitoring are essential. Guidelines must complement legislation to enable innovation while maintaining high standards of safety and effectiveness. Independent quality assurance resources and real-world testing environments, such as those being developed under initiatives like the Testing and Experimentation Facility for Health AI and Robotics (TEF-Health), can support more dynamic development.
Promote public–private collaboration. Public–private partnerships should move beyond consultation to active codevelopment of evaluation standards and monitoring frameworks. Such collaboration is vital to ensure that regulatory practices keep pace with AI innovation while safeguarding patient trust and public health objectives.
The WEF-BCG research also emphasizes the importance of global coordination. Divergences in AI regulatory approaches across regions—especially between the Global North and Global South—risk creating barriers to the scalable deployment of AI in health care. Capacity-building efforts, particularly in underresourced health systems, are crucial to ensure equitable benefits from AI advances.
Ultimately, the future of AI in health care must be grounded in adaptability, transparency, and shared responsibility. By strengthening evaluation processes, building technical capacity, and fostering structured public–private collaboration, health systems can unlock the transformative potential of AI while upholding patient safety and trust and ensuring broader access to innovation.
The path forward demands continuous innovation not only in technology but also in regulation and system design. The time to act is now, to ensure that AI fulfils its promise of delivering better health outcomes for all.
The Future of AI-Enabled Health: Leading the Way
As artificial intelligence and digital technologies fundamentally change the way that industries worldwide do business, health care leaders have a choice to make: Embrace transformative change that profoundly alters how health care is accessed and delivered, or proceed with incremental changes and tools that improve the practice of health care at the margins?
Artificial intelligence has the potential to drive tremendous improvements in health outcomes worldwide and reduce inequities in care. Still, to date the health care sector has been relatively slow to adopt AI at scale.
The World Economic Forum and BCG interviewed more than 75 experts in the public and private health care sectors to better understand the issues hindering progress. Three central but surmountable challenges emerged:
- AI lacks appeal for policymakers and industry leaders because there is no compelling strategy that aligns AI efforts with broader health goals and political priorities.
- Strategic health care goals aren’t integrated with technology choices, leading to missed opportunities to use AI for systemic improvement in health care delivery and outcomes.
- In a fragmented regulatory landscape, a lack of transparency and accountability around AI undermines public trust.
To scale AI and achieve transformative change, health care leaders must take several steps:
- Deliver short-term AI benefits that demonstrate returns and encourage long-term investments.
- Align public and private sector objectives and priorities around AI and agree on how to best share the value it creates.
- Prioritize shared infrastructure investments, such as digital public infrastructures that, where feasible, align private sector services with public good solutions.
- Train leaders at all levels in the technical aspects of health care to provide the skills necessary to make strategic decisions about AI’s potential, limits, and risks rather than deferring technology decisions to others.
- Build trust in AI by improving post-market surveillance to identify AI-related risks, and consider establishing AI ethical committees and principles.
- Advocate for locally controlled data that is globally connected and patient centered to drive innovation and ensure patient safety and privacy.
AI can be a revolutionary force in health care. For that to happen, however, public and private sector leaders will need to act in a new spirit of cooperation focused on creating a sustainable AI health ecosystem. This WEF-BCG report describes the major challenges health care leaders face and the pivotal steps they can and must take to achieve transformative change.
Accelerating the Digital Transformation of Health Care Systems

Ben Horner, Johanna Benesty, and Jennifer Clawson
The need for digital health innovations is at an all-time high. Health systems around the world are facing record-high health care costs and severe workforce shortages as demand for care is growing—and as inequities persist. Consider these statistics:
- Approximately $1.8 trillion in health care spending is wasteful.
- By 2030, we will face a shortage of more than 10 million health care workers.
- Chronic conditions, which already account for 70% to 90% of total health spending in the EU and US, are becoming more prevalent.
- Health care access and outcomes vary massively between and within countries.
To solve these challenges, we must invest in a digital health care transformation. Many digital health innovations are already available on the market, and leading health systems are leveraging these innovations to optimize the patient journey and help health care workers be more efficient and effective. However, we have yet to see transformative impact of digital, data, and AI across health care systems.
We need to approach the problem differently. Health care system leaders must first define a robust and forward-thinking digital strategy, and then they must put in place the key enablers that will allow digital health to scale. These enablers include:
- Developing digital health capabilities
- Building a robust digital health care infrastructure
- Unlocking value from data
- Aligning incentives among diverse stakeholders and ensuring sufficient funding
- Creating fit-for-purpose regulations and policies
Delivering on the promise of digital and AI in health care will also require an ecosystem mentality. No single actor can bring about the digital health transformation. Stakeholders from all sectors must come together to solve our biggest health care challenges. A robust ecosystem can tackle our most entrenched problems and scale solutions quickly in ways that individual digital solutions cannot. Public-private collaboration will be especially important as we search for innovative solutions to complex health care challenges and put in place the enablers needed for system transformation.
In this report, we lay out the major health care challenges that digital can address; identify the key enablers that need to be in place to accelerate the adoption and impact of digital solutions; share best practices and success stories; and chart a path forward to accelerate the journey toward a successful digital transformation in health care.
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