Artificial Intelligence (AI) is rapidly shaping health systems, with strong potential to enhance surveillance, decision-making, and resource use. Across the Middle East and North Africa (MENA) region, however, its adoption in public health remains uneven, constrained by gaps in governance, infrastructure, and workforce capacity.

To address these challenges, EMPHNET hosted the 53rd session of its WEBi Series, titled “Investment in Artificial Intelligence to Promote Public Health in the Middle East and North Africa: Current Status and Future Challenges,” on April 21, 2026, with more than 330 participants in attendance.

The session brought together regional and global experts to explore how AI can move from innovation to practical, system-level implementation in public health. An analytical review developed for the session further examined the current landscape, challenges, and opportunities across the region.

This webinar was organized based on a recently published analytical review on the current status and future challenges of AI in public health across the MENA region, which informed the session’s discussions and framing. You can read it here.

Opening Remarks

Moderated by Prof. Yousef Khader, Director of the Center of Excellence for Applied Epidemiology (CEAE) at EMPHNET, the session opened by outlining the core objectives of the webinar and positioning AI as a strategic priority for strengthening public health systems in the region.

AI in the EMR: Rapid Growth, Uneven Progress

Dr. Mohannad Al-Nsour, Executive Director of EMPHNET, presented an overview of the current landscape of AI in public health across the Eastern Mediterranean Region (EMR).

He highlighted that while AI is transforming health systems globally, the EMR remains a mid-tier but rapidly advancing region, marked by significant disparities between countries. Countries such as Saudi Arabia, the UAE, and Qatar are leading in AI integration, supported by strong national strategies and investments, while others remain at earlier stages due to infrastructure and capacity constraints.

He emphasized that fragmentation, uneven digital infrastructure, and gaps in governance frameworks remain key challenges, with a risk of widening inequalities if AI is not implemented responsibly. He also highlighted EMPHNET’s role in bridging the gap between AI innovation and public health practice through capacity building, country support, and regional coordination.

Bridging the Gap Between Innovation and Implementation

Prof. Radwan Qasrawi, CEO of B-CITE and Professor of Information and Communication Technology Engineering at Al-Quds University, focused on the gap between AI research and its practical application in public health. He highlighted that despite growing interest, most AI applications in the MENA region remain concentrated in clinical and curative care, with limited integration into public health systems.

He stressed that moving from pilot projects to scalable solutions requires stronger digital foundations, improved data systems, and a shift toward preventive and population-based approaches. He also emphasized the importance of low-cost, scalable solutions, such as digital platforms and community-based tools, as practical entry points for resource-constrained setting.

Governance, Inequality, and System Fragility

Prof. Zakaria Belrhiti, Associate Professor of Community and Preventive Medicine at the Mohammed VI University of Sciences and Health (UM6SS), brought a systems and governance perspective, framing AI adoption within the broader realities of the MENA region. He described the region as operating within a complex and fragile context shaped by conflict, displacement, and health system pressures, where public health systems are often marginalized in favor of curative care.

He emphasized that AI governance is highly fragmented, with key challenges including weak regulatory frameworks, digital divides, and limited workforce capacity. A key message from his presentation was the need to “democratize” AI, ensuring equitable access, inclusive governance, and shared benefits across countries and populations.

Explainable AI and the Future of Public Health Training

Dr. Mostafa Ali, IEEE Senior Member and Professor of Computer Information Systems at the Jordan University of Science & Technology (JUST), introduced the concept of explainable AI (XAI) and its role in strengthening public health training and decision-making. He highlighted a critical gap in current AI systems: while they are strong in prediction, they often lack transparency and do not adequately support human decision-making.

His work explores the integration of AI with immersive technologies such as virtual reality, enabling more advanced, data-driven training environments. These systems can provide real-time, explainable feedback, helping users understand not only outcomes, but also the reasoning behind them.

Learning from Global Experience: A Regional Approach to Collaboration

Mr. Tiago Masrour, General Manager at Centro Ciencia & Vida, shared practical insights from Latin America, highlighting how similar challenges such as data fragmentation, resource constraints, and governance gaps have been addressed through collaborative models. He introduced the “governance before algorithms” approach, emphasizing the importance of building strong institutional frameworks, shared methodologies, and communities of practice before scaling AI solutions.

He also presented federated and decentralized approaches to data use, which allow countries to collaborate and share insights without compromising data sovereignty. His key message was that investment in AI is ultimately an investment in collaboration, requiring trust, shared standards, and coordinated action across countries.

Audience Discussion: From Hype to Implementation

The discussion reflected strong engagement from participants, focusing on practical, ethical, and system-level challenges. Key points included concerns about widening inequalities, governance gaps, data availability and quality, and the need to strengthen workforce capacity and AI literacy. Participants also emphasized the importance of aligning AI investments with real public health needs and ensuring trust and applicability in different contexts.

Key Takeaways

The session highlighted several key messages:

• AI offers strong potential to enhance public health systems, particularly in surveillance and decision-making
• Adoption across the MENA region remains uneven, driven by disparities in infrastructure, governance, and capacity
• Governance and ethical frameworks are essential to ensure safe and equitable use of AI
• Strengthening digital systems and workforce capacity is critical for implementation
• Practical, scalable solutions must be prioritized, particularly in low-resource settings
• Regional collaboration is essential to accelerating progress and reducing disparities
• AI must be aligned with public health priorities

In closing, Prof. Khader emphasized the importance of collaboration and invited partners and stakeholders to engage in advancing AI-driven public health in the region.

The session reinforced a clear message: the priority now is ensuring responsible, equitable, and practical implementation of AI within public health systems.

Watch the webinar here.

Explore more sessions from the EMPHNET WEBi Series here.