This session explores how Artificial Intelligence (AI), Machine Learning (ML), and related innovations can realistically support digital health systems and DHIS2 implementations. The discussion will focus on practical use cases, lessons learned, opportunities and limitations of emerging technologies, and how innovation can strengthen data collection, interoperability, and decision-making in low- and middle-income country contexts. The session also aims to encourage critical discussion around sustainability, governance, ethics, and local ownership as AI capabilities continue to evolve across the global health ecosystem.
View the slides for this session here.
This session explores how Artificial Intelligence (AI), Machine Learning (ML), and related innovations can realistically support digital health systems and DHIS2 implementations. The discussion will focus on practical use cases, lessons learned, opportunities and limitations of emerging technologies, and how innovation can strengthen data collection, interoperability, and decision-making in low- and middle-income country contexts. The session also aims to encourage critical discussion around sustainability, governance, ethics, and local ownership as AI capabilities continue to evolve across the global health ecosystem.
View the slides for this session here.
Auditorium 1 The DHIS2 Annual Conference oslo2026@dhis2.org
Technical Issues?
If you're experiencing playback problems, try adjusting the quality or refreshing the page.
Questions for Speakers?
Use the Q&A tab to submit questions that may be addressed in follow-up sessions.
