Frontline First: Investing In and Designing AI for Real‑World Care

Join us to shift the focus of AI for health toward practical decision support for primary care teams, community systems, and self-care.

Global conversations on artificial intelligence in health often begin at the top of the system, in hospitals, specialist care, and high-tech environments. We want to speak to and from where most care decisions are actually made: in homes, communities, primary care facilities, and by frontline health workers operating under pressure, uncertainty, and constraint.

Frontline health workers, including community health workers, nurses, midwives, and primary care providers, are central to primary health care systems and to progress toward Universal Health Coverage. They make high-stakes decisions every day on triage, referral, treatment initiation, follow-up, risk identification, supply availability, and community engagement, often without real-time guidance, adequate supervision, or reliable information.

At the same time, WHO guidance on AI for health emphasizes the need for transparency, accountability, inclusion, and the protection of public interest as AI becomes embedded in health systems.

The WHO guidance on self-care further recognizes that health outcomes and system resilience depend not only on formal service delivery, but also on the ability of individuals and communities to make informed decisions about health and care. This creates perhaps the most impactful zone of opportunity for AI, to reduce uncertainty, disrupt inequities, improve decisions, and strengthen care where health outcomes are won or lost.

Join us to challenge the current center of gravity in AI for health. Share views and thoughts to make the case that the next frontier of impact is AI as a practical decision-support layer for primary care teams, community systems, and self-care pathways.

Convened with Viamo, this event will bring together policymakers, technology leaders, frontline implementers, funders, and global agencies to confront a provocative but urgent question: Are we making the right investments in AI for health, or are we funding what is easiest to build rather than what health systems most need?