International cooperation in AI (IA)

Expected outcome

Project results are expected to contribute to one of the following outcomes:

• Faster uptake of tailored and enhanced AI solutions at innovation hubs in low- and middle-income countries by training and optimising them with local data and applied research.
• Easier large-scale deployment of local AI solutions in low and middle-income countries by increasing the efficiency of system demonstration in relevant, operational environments.
• Strengthened local innovation ecosystems that foster sustainable socio-economic impact by addressing key societal challenges in areas such as education, healthcare, agriculture, and environmental sustainability.

Scope

System prototype, testing, validation, and demonstration in operational environment aligned to EU initiatives, such as the International Digital Strategy for the EU and the AI Continent Action Plan, to strengthen local AI ecosystems in African countries fostering responsible AI development, north-south digital cooperation on AI, and sustainable AI innovation.

The main goal is to support the digital transition and foster inclusive economic and social transformation of partners globally by adapting and applying innovative solutions, research areas and capabilities developed in Europe to low- and middle-income countries.

This Innovation Action will focus on accelerating the uptake of and access to AI solutions by local innovation hubs in these countries, better enabling their practical implementation and future market deployment in operational environments. Proposals should consider synergies and complementarity of ongoing research and innovation activities in the policy areas of international partnerships, digital and infrastructure like the Digital for Development Hub and AI for Public Good, and may follow an approach like Living Labs. Proposals should also support the European Union’s Global Gateway strategy to boost smart, clean, and secure connections in digital, energy and transport sectors, and to strengthen health, education and research systems across the world. Proposals should enable AI technologies that are locally relevant and sustainable, empower local communities and platforms, and reflect the EU’s emphasis on sustainable and resilient global partnerships.

The proposals must support digital partnerships and international digital cooperation to promote an approach to AI that enhances human well-being and societal progress through:

• Support for gathering of and access to local data in line with EU’s data strategy for the training and optimisation of existing AI algorithms developed in initiatives like AI for Public Good and GenAI for Africa.
• Establishment and support of Living Labs within local innovation hubs in low-income countries, fostering co-creation spaces where community members, researchers, entrepreneurs, and policymakers can collaboratively tailor, enhance, test, and iterate AI-driven solutions. These Living Labs will serve as platforms for experiential learning, inclusive participation, and sustainable technology adoption.
• Tailored and contextualized AI-based solutions developed through a bottom-up approach, driven by the specific needs of low-income communities. These solutions will be trained and adapted using local data sources, enabling meaningful knowledge transfer and empowering local stakeholders with relevant and actionable technologies.
• Contribution, where possible, to solving global sustainable development challenges, especially climate and agriculture, biodiversity, health and humanitarian needs, education.
• Fostering an enabling innovation environment with reinforced talent pipelines and technological transfer of AI algorithms and solutions to local innovation hub.
• Full testing and validation of the solutions in real-life with scenarios and initial support to large-scale deployment in low and middle-income countries.

Capitalise from existing EU initiatives like the call GenAI for Africa from HE WP25, the Global Gateway, and Smart Africa to up-scale the deployment of solutions in low-income countries.