Global call for AI for health case studies
Third meeting of the Global Initiative on AI for Health | Hangzhou, China | 16–18 September 2026
Background
This global call is being launched jointly by the International Telecommunication Union (ITU), the World Health Organization (WHO) and the World Intellectual Property Organization (WIPO) through the Global Initiative on AI for Health (GI-AI4H), which brings the three UN agencies together to advance responsible, scalable and equitable AI for health. The call will contribute to preparations for GI-AI4H’s third annual meeting, to be held in Hangzhou, China, from 16 to 18 September 2026.
Objective
We are seeking a geographically diverse range of short case studies describing how AI has been implemented in real-world health settings. The case studies should relate to primary health care, health system strengthening or progress towards universal health coverage, and should highlight transferable lessons that others could apply in different contexts.
Outputs
Selected submissions will be refined into short case studies and published in the report of the third annual meeting. A small subset of contributors may also be invited to present their work during the meeting in Hangzhou, subject to confirmation and logistical feasibility.
Evaluation criteria
We will assess submissions against criteria including the strength of the supporting evidence; relevance to primary health care, universal health coverage and health system strengthening; health system or public health value; responsible AI governance; and transferable lessons. The final selection may also take into account the geographic balance and thematic diversity of the case studies.
The submission, selection, presentation or publication of a case study does not constitute endorsement by ITU, WHO, WIPO or GI-AI4H.
How we will use your submission
The information you provide will be reviewed by the GI-AI4H Secretariat and authorized review partners to select submissions for inclusion as short case studies in the report of the third annual meeting and, where applicable, for presentation during the meeting. We may contact you to clarify details or to work with you in refining your submission for publication.
Contributors to selected case studies will be appropriately acknowledged and given an opportunity to review the final text before publication. Submission of this form does not guarantee selection, presentation or publication. Insights from all submissions may be used in aggregate to inform the report’s broader findings and transferable lessons. Any identifiable use of your submission in public materials will be discussed with you in advance.
Data protection and confidentiality
The information you provide through this form will be used only for the purposes described above and will be accessible to the GI-AI4H Secretariat and authorized reviewers involved in the assessment and publication process. It will be handled securely and in accordance with applicable data-protection requirements.
Please do not include confidential, proprietary, personal or otherwise sensitive information that you are not authorized to disclose. Any personal contact details you provide will be used only to administer the call and to contact you regarding your submission. They will not be included in public outputs or shared beyond the authorized review and project teams without your consent.
No identifiable information about individuals, institutional attribution or direct quotation from your submission will be made public without your agreement. By submitting this form, you acknowledge that the information provided may be reviewed as described above and that you may be contacted for clarification or follow-up.
Instructions
- Submit one form for each case study.
- Complete the form in English and use plain language suitable for a mixed audience. Avoid acronyms wherever possible. Where an acronym is necessary, spell it out on first use.
- Complete all required fields and observe the stated word limits. Responses should total no more than approximately 1000 words, excluding contact details, references and declarations.
- Focus on what was done, what changed and what was learned. Do not submit proposals or aspirational plans. Clearly distinguish observed results from estimates or projections.
- Do not include confidential or proprietary information, or personally identifiable information about patients or other third parties. Anonymize sensitive details and submit only information and materials that you are authorized to share.
- Submit the completed form by 23:59 CEST (UTC+2) on Thursday, 20 August 2026.
