Expanded edition of the paper on AI in national research ecosystems focuses on the Global South

The latest edition features new case studies and updates to previous analyses, offering fresh insights into how different nations — both large and small economies — are prioritizing AI in their scientific and research strategies. The study serves as a valuable resource for policy-makers, research leaders, and academic institutions, providing comparative perspectives and examples of national AI priorities.

• Australia*: Preparing for human-centric use of AI
• Benin: Anticipating the impacts of artificial intelligence on West Africa’s aspiring digital
• Brazil*: Reaping the benefits of AI with some cautionary notes
• Cambodia: Seeking artificial intelligence approaches to national research missions
• Chile: Finding possibilities to apply artificial intelligence in an existing research financing ecosystem  
• China*: Promoting the artificial intelligence for science approach  
• Colombia**: Scientific ecosystems and enablers of artificial intelligence
• Dominican Republic**: ENIA: a roadmap for creating a knowledge economy based on artificial intelligence
• India: Gaining insights into transformative technologies and their social integration
• Malaysia*: Enabling the Fourth Industrial Revolution  
• Mexico: Creating a national lead agency for artificial intelligence
• Oman: Fostering Innovation through an Executive Program
• Pakistan**: Building a robust, resilient digital ecosystem 
• Palestine**: Adapting the science landscape for artificial intelligence
• Panama**: Assessing the artificial intelligence ecosystem .
• South Africa**: Adopting artificial intelligence for all citizens
• Uruguay: Following a roadmap to prepare national science systems for artificial intelligence
• Uzbekistan: Building the right conditions and skills for artificial intelligence

* Updated country case study
** New country case studies

Key findings highlight that AI adoption in science frequently prioritizes sectors such as agriculture, healthcare, and education. However, the research also underscores country-specific applications, ranging from governance and justice systems to smart cities. Additionally, many nations are concentrating their AI efforts on select focus areas — such as computing infrastructure and workforce upskilling — highlighting the challenge of achieving comprehensive AI integration.

Beyond these insights, the paper raises critical issues surrounding AI for science, including the need for better data strategies and the importance of regional and transnational collaboration. To further explore these challenges, the ISC is preparing three clarification papers that will delve deeper into these themes.

Looking ahead, the Centre for Science Futures plans to release a third edition of the paper by mid-2025, continuing its work to refine and expand the understanding of AI’s transformative impact on science systems.

This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada. The views expressed herein do not necessarily represent those of IDRC or its Board of Governors.