The proposals should address one or more of the following:

• Agriculture optimisation: GenAI can analyse satellite imagery and sensor data to monitor state of crops, soil conditions, and weather patterns, enabling farmers to boost crop yields and enhance food security through sophisticated predictive analytics and efficient resource management like water and pesticides. This is crucial to mitigate climate change and poor irrigation infrastructures in some areas of Africa.
• Healthcare: GenAI can diagnose diseases from medical images and patient data, enhancing healthcare in remote areas; forecast disease outbreaks and aid in preventive planning, and with the help of chatbots and virtual assistants can offer medical advice and connect patients with doctors, expanding telemedicine services, making healthcare more accessible to remote populations. Particular attention should be paid to the gender dimension in addressing AI biases, sex-specific healthcare needs, and intersecting gender and racial inequalities in health and access to health services.
• Infrastructure and urban planning: GenAI optimises energy usage, integrates renewables, and ensures efficient distribution, while managing water (including groundwater but also rainfall use) and waste (e.g. plastic reduction and reuse) effectively for sustainability, and enhancing safety with real-time incident detection. It also provides support for reconstruction following natural or human-made disasters. This is vital for some African communities with scarce natural resources like water and facing high temperatures by using Digital Twins on urban and rural areas. All these technological solutions depend strongly on the existence and quality of connectivity infrastructure, as a key enabler for unlocking the Digital and Green Transition.
• Digital Skills and learning: Generative AI can personalize learning paths, create multilingual educational content, and offer on-demand virtual tutoring, benefiting rural communities with low resources and fully relying on mobile phones to access online services. Additionally, adaptive learning platforms can use data analytics to tailor teaching, while engineers craft queries to help AI models understand local languages and nuances to set up conversational chatbots for local communities.

The proposals should approach these objectives by:

• Conducting an evidence-based analysis to identify particular needs in Africa that GenAI technologies could solve, for one or several of the topics mentioned above.
• Identifying solutions on GenAI developed in the EU that could be applied in Africa for one or several of the topics mentioned above.
• Based on existing EU-based solutions and particular needs, developing and integrating generative Artificial Intelligence models and algorithms specifically adapted for one or several of the abovementioned key areas.
• Involving and supporting start-ups and local networks in 3 to 5 locations in Africa to create innovative solutions to uniquely African challenges in those areas based on GenAI. Co-creation and living lab methodologies should be explored to boost social uptake of proposed solutions. Living labs are ecosystems of experimentation and open innovation, with a systematic approach to co-creation among their users, whether they are researchers, businesses, civil society or public administrations. These open innovation spaces will enable researchers and local actors from the public and private sectors work together using digital technologies to co-create knowledge and solutions that respond to their societal needs, while improving territorial cohesion.
• The approved projects should take into account the AI Act and GDPR as the main legal frameworks to ensure data protection of the data used within third countries.