Strategy: Six calls to action to drive value creation4 In the six steps outlined in this section, leaders are called on to cooperate in building and shaping a sustainable ecosystem to strengthen the positive impact of AI in healthcare and to increase trust. The three main challenges described in Section 3 are interconnected in a vicious circle: technical problems and distrust discourage leaders from risking political capital on AI, and leaders currently focus on other priorities and do not engage in strategic technology decisions to scale the impact of AI or prioritize the work of building trust. One way to break this is to change leaders’ behaviour towards AI and digital health. From dreaming of breakthroughs to delivering near-term benefits that accelerates a long-term vision AI in health is a complex and non-homogenous space: operational AI applications focus on productivity and processes, such as supply chain management, without directly affecting patients, while clinical applications fundamentally change the way healthcare is delivered. Public leaders should start with operational applications of AI in health and work with private leaders to make sure the return on investment is measurable in a short time frame. Lessons can be learned from other industries that inspire champions “on the ground” to start small, learn and move with agility, while also ensuring outcomes are achieved, including tracking of responsible key performance indicators for AI. Operational AI applications can significantly reduce caregiver workloads and improve the efficiency of health systems, creating short-term value that will build positive momentum for more substantial, long-term investments and set the scene for deeper transformations. From the private sector progressing technology independently to public– private ecosystems driving shared objectives and benefits For medical applications, the landscape is marked by a lack of agreed priorities, no consensus as to the value at stake, uncertainty about how to share potential value creation and, most importantly, no short-term ROI. The right way forward here is for public and private leaders to align on priorities, understand the opportunities and risks of AI medical applications and agree on how best to share the value created. This approach is common in other policy areas, such as defence, and health leaders should adopt similar strategies. It is particularly true for clinical transformation at scale, where public and private actors must collaborate closely, align on common goals and establish clear mechanisms for value sharing, acknowledging that this will take different forms in different political and economic contexts. While this process will take time, it will ultimately help the ecosystem hedge against investments that could become impossible to scale due to unmet requirements, such as reimbursements. From fighting on infrastructures to winning on services The competition over infrastructure is intense and dilutes the efforts of both public and private actors, exacerbating a significant financing gap in digital and AI infrastructure. Leaders must prioritize common foundations, especially DPI, when making all technical choices. Public leaders should view these as critical investments in the future and incorporate them in their vision for two reasons. First, encouraging cooperation on infrastructure pushes the private sector to differentiate through services, promoting a competitive market focused on high-value offerings. Such collaboration enhances efficiency and equity, enabling faster implementation, cost reduction and broader access. Second, promoting blended financing for AI infrastructure is essential: between 2018 and 2023, private investments in infrastructure grew by $700 billion, or 18% annually, outpacing traditional private-equity buyouts. Private investors can help close the significant financing gap and ensure equitable access to key digital enablers, but only if leaders prioritize this as a key agenda item.1 23 The Future of AI-Enabled Health: Leading the Way 23

The Future of AI Enabled Health 2025