Preparing national research ecosystems for AI: strategies and progress

Key takeaways

• Ethical principles and human-centric approaches to AI are informing Australia’s emerging framework for AI governance. The number of tertiary education offerings for AI have increased in Australia and are complemented by an initiative to attract and train job ready AI specialists.
• While active programs to enhance diversity in Australia›s STEM workforce exist, they are not specifically tailored to address AI. Additionally, there is a recognized need to enhance ethical competence and raise awareness of human rights in AI-related scientific endeavours. However, more customized resources for the science sector are required.
• Other challenges remain to be addressed such as the high-performance and data computing infrastructure needed for AI and AI-enabled science and the implementation of FAIR and CARE data principles.

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• Edition 1 (2024)
• Edition 2 (2025)

Key takeaways

• Digital infrastructures and platforms have been put in place since 2016 as part of the Beninese vision as the hub for digital services of West Africa. Institutes in the country have initiated AI training and education programs for the young generation.
• Challenges around data collection, preparation, access, storage and governance need to be addressed for proper operation of AI systems. Data protection and fundamental rights as well as data governance also raise legal, regulatory and ethical challenges

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Key takeaways

• The need to facilitate AI research and development has driven the Brazilian government to enact legislative reform and a key achievement is the partnership of the Ministry of Science with national funders and experts for the creation of AI Applied Research centres.
• Challenges in the country include a gap in AI literacy and education as well funding for AI research. There is also worry on the stagnation of the national AI strategy and bills of law that could hinder science and research priorities, foster uncertainty among researchers and limit international collaboration.

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Key takeaways

• The collective efforts in developing cloud-based services in the country has been supported by local actors across different sectors. The National Research Agenda 2025 has identified the national challenges and has put a plan to address these challenges.
• There is limited funding and capacity for research in Cambodia as well as weak alignment between research work and national challenges. Cultural caution around uncertain technologies makes a part of why education is predominantly prioritized for engineering and accounting.
• Among the immediate priorities are strengthening of the infrastructure for data and
  computing power as well as upskilling and expansion of AI practitioners.

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Key takeaways

• Challenges in Chile around AI for science are multifaceted; primarily there is a lack of funding, resources, infrastructure and capacity and skills for AI.
• Priorities for AI have not been identified at the national scale and universities may be working in silos. Whether a unified vision for AI for science will exist in the near future in Chile is not yet clear.

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Key takeaways

• The government in China is supporting the integration of AI across different fields of science through programs and infrastructure.
• China is active on the international front regarding AI technologies and has achieved the development of platforms and software supporting AI.

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• Edition 1 (2024)
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Key takeaways

• Colombia is a regional leader in AI in Latin America, but faces significant challenges in developing appropriate infrastructure, data availability and digital skills.
• The Government of Colombia envisions AI as a key tool in tackling the country’s most pressing challenges.
• Multiple programmes and initiatives are underway to expand connectivity, improve digital literacy and advance the development of AI with a social impact.

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Key takeaways

• The National Artificial Intelligence Strategy (ENIA) of the Dominican Republic is a driver of national development – facilitating the creation of AI infrastructure that works in the public interest, and promoting business growth to generate more opportunities and prosperity for citizens.
• The ENIA covers everything from human talent and technology development to regional collaboration and ethical governance of AI, ensuring effective and responsible implementation.
• The Dominican Republic is emerging as a leader in the adoption and development of AI in Latin America and the Caribbean, promoting regional collaboration and establishing ethical standards.

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Key takeaways

• Development of online platforms and AI supporting software tools in India are part of its vision to become the hub for software in the Global South. Achievements in the country include the establishment of Centres of Excellence and upskilling initiatives to advance capacity for AI.
• Streamlining and coordinating the work of the newly established Centres of Excellence as well as the lack of private-public partnerships are challenges in the country which are currently being addressed.

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Key takeaways

• Malaysia aims to become a high-tech nation by 2030 through the strategic integration of AI, as set out in key policies including the National Science, Technology and Innovation Policy 2030–2021 and the National Artificial Intelligence Roadmap 2021-2025. These policies promote the adoption of AI in sectors like health care, education, agriculture and finance, to boost economic development and societal well-being.
• Major global technology companies like Oracle, Google, Microsoft, NVIDIA and Amazon Web Services have invested billions of dollars in Malaysia to enhance AI and cloud computing infrastructure, underscoring Malaysia’s role in the global AI landscape.
• A National AI Office, newly established in 2024, aims to position Malaysia as a key AI player in the Association of Southeast Asian Nations (ASEAN) and globally, and demonstrates Malaysia’s commitment to AI innovation.

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• Edition 1 (2024)
• Edition 2 (2025)

Key takeaways

• The setting up of a national AI strategy in Mexico has been mandated through the creation of a Mexican Agency for the Development of Artificial Intelligence in 2023. Concurrently, previous multisectoral initiatives in the country are convening discussions on and development of AI technologies with an important role of universities.
• Challenges in Mexico lay in spearheading the next steps of the newly founded agency and focusing on local AI technology development rather than relying on foreign technology.

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Key takeaways

• The Ministry of Transport Communications and Information Technology is leading the national AI strategy and its implementation in Oman. Economic objectives through Oman Vision 2040 are the predominant drivers for AI technology developments.
• Partnerships between the ministry and universities and other sectors have been created for AI training programs and initiatives.

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Key takeaways

• Pakistan is actively developing its use of AI in multiple sectors and has instituted many initiatives to facilitate progress.
• Programmes are prioritizing development of the necessary policies, research, skills and infrastructure to disseminate AI throughout the country.
• Challenges to the widespread adoption of AI technologies remain, particularly in the areas of data quality and availability, and responsible and ethical use.

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Key takeaways

• The introduction of an AI National Strategy and using the UNESCO Readiness Assessment Methodology tool mark significant achievements for Palestine.
• Capacity-building programmes and infrastructure development are underway, aiming to develop local expertise and create a supportive environment for AI research and applications.
• There is a pressing need to develop policies and frameworks to support and expand AI research and development in Palestine.

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Key takeaways

• Panama faces multifaceted challenges to the successful adoption of AI across a range of industries and sectors.
• A draft Bill to regulate the use, development and application of AI in Panama, and a new national strategic plan for science and technology for 2029–2025 are aiming to address some of these challenges.
• A national project, INDICATIC, is focusing on data processing, with AI as a critical component, and encompasses research, innovation and training.

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Key takeaways

• South Africa has embraced AI by establishing: the Presidential Commission on the Fourth Industrial Revolution; the Artificial Intelligence for Africa Blueprint and other regional frameworks; a digital and future skills training programme for 500,000 participants; the Centre for Artificial Intelligence Research, and the Artificial Intelligence Institute of South Africa; and initiatives to reduce data costs and improve internet penetration, so that all South Africans can benefit from the AI revolution.
• The Department of Science and Innovation’s National Integrated Cyber Infrastructure System, together with supercomputer research into AI, means that South Africa is poised to harness big data and drive future scientific and industrial growth.
• A key challenge is the need for a comprehensive national AI strategy to guide and coordinate efforts across various sectors in South Africa.

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Key takeaways

• The Roadmap for Data Science and Machine Learning developed in Uruguay in 2019 highlights the role of universities, public-private partnerships and civil society. National and international investment have supported AI projects in the country since 2017.
• Uruguay is leading regional events and initiatives on AI placing it as a leader in the region.
• Among the immediate next steps in the country are capacity building and upskilling and AI education.

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Key takeaways

• Presidential resolution enabling policy frameworks and strategies for AI in Uzbekistan have been put in place since 2020. Among the country’s strategic goals is training the young generation, it has therefore set a goal to train one million Uzbeks through an online training platform.
• A new agency for Ai development has been founded to monitor and implement AI technologies across all sectors.
• The recruitment of the newly trained generation in coding and the infrastructure to support AI work are next steps for the country.

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