Announcement of the National AI Research and Development Plan During AI Research Week

Singapore has made a bold commitment to artificial intelligence by announcing an investment exceeding S$1 billion in public AI research from 2025 to 2030. This initiative, known as the National AI Research and Development Plan (NAIRD), was unveiled by Minister for Digital Development and Information Josephine Teo at the gala dinner of Singapore AI Research Week 2026 on January 24. The week-long event, running from January 19 to 27, features over 40 activities marking the 40th anniversary of the Association for the Advancement of Artificial Intelligence (AAAI), coinciding with AAAI 2026 in Singapore.

This substantial funding more than doubles the previous NAIRD allocation of over S$500 million, underscoring Singapore's determination to position itself as a global AI hub. The plan aligns with the broader Research, Innovation and Enterprise 2030 (RIE2030) framework, which allocates S$37 billion to advance national research capabilities, particularly in AI, data, and compute infrastructure.

Core Pillars of the NAIRD Initiative

The NAIRD plan is structured around three interconnected pillars designed to elevate Singapore's AI ecosystem. First, it emphasizes fundamental AI research, tackling cutting-edge challenges like trustworthy AI systems that mitigate risks such as bias, hallucinations, and adversarial attacks. Second, it prioritizes the creation of Research Centres of Excellence (RCEs) within public research institutions to foster groundbreaking discoveries. Third, it focuses on applied AI research tailored to high-impact sectors, ensuring research translates into real-world solutions.

Minister Teo highlighted the need for 'bilingual research talents' proficient in both AI techniques and domain-specific knowledge to bridge theory and practice. This approach aims to not only produce high-quality publications but also drive innovation that benefits economy and society.

Fundamental AI Research: Pioneering Trustworthy Systems

At the heart of NAIRD is investment in fundamental research to address AI's inherent risks. Topics include developing safeguards for AI models, enhancing system security, and achieving resource-efficient algorithms amid growing computational demands. These efforts are crucial as AI models scale, increasing potential for misuse or errors.

Singapore's emphasis on responsible AI builds on its Model AI Governance Framework, updated in 2020, which promotes fair, ethical, accountable, and transparent AI deployment. By funding blue-sky research, NAIRD seeks to generate seminal papers that influence global standards, positioning Singapore researchers at the forefront of AI safety discourse.

For instance, ongoing work at institutions like A*STAR explores privacy-enhancing technologies (PETs), enabling secure data sharing for AI training without compromising confidentiality. This could lead to breakthroughs in federated learning, a hot topic in recent NeurIPS and ICML conferences.

Establishing AI Research Centres of Excellence

NAIRD will fund multiple RCEs hosted in public research entities, including universities and A*STAR. These centres will attract top local and international talent, providing state-of-the-art facilities for collaborative, long-term projects.

NTU Singapore, already home to several RCEs in areas like quantum technologies, is poised to lead in AI. NUS, ranked 8th globally in QS World University Rankings 2026 and top in Asia for many subjects, boasts the NUS Artificial Intelligence Institute, a key player in AI research. These centres will incubate PhD students and postdocs, boosting publication output in top venues like AAAI, IJCAI, and Nature Machine Intelligence.

Experts anticipate RCEs will produce high-impact papers, with case studies from prior initiatives showing 30-50% increases in citations per researcher.

Applied AI Research in Priority Sectors

NAIRD bridges academia and industry through applied research in manufacturing, biomedical sciences, precision medicine, and public services. For example, AI-optimized drug discovery at biomedical hubs could accelerate therapies, while smart manufacturing models enhance productivity.

In biomed, collaborations between NUS Yong Loo Lin School of Medicine and A*STAR have yielded papers on AI-driven diagnostics, reducing error rates by 20%. Public sector applications, like predictive analytics for services, promise efficiency gains, with prototypes already tested during COVID-19 response.Learn more on CNA

• Manufacturing: AI for predictive maintenance, cutting downtime 25%.
• Biomed: Genomics analysis, speeding personalized medicine.
• Public services: Chatbots and forecasting for better governance.

Talent Development: Tripling AI Practitioners to 15,000

Under NAIS 2.0, NAIRD supports tripling Singapore's AI workforce to 15,000 practitioners by 2030. This includes scholarships, industry attachments, and attracting global experts to universities.

Higher education institutions like NUS and NTU offer specialized AI degrees, with NTU topping international AI program rankings. Programs emphasize interdisciplinary training, producing graduates ready for R&D roles. For aspiring researchers, check research jobs in higher ed or Singapore academic opportunities.

Singapore Universities' Role in AI Research Surge

NUS and NTU dominate Singapore's AI research landscape. NUS ranks 17th globally in THE Rankings 2026 for research excellence, with strong AI output. NTU's AI programs edge global peers, fostering open-source contributions.

A*STAR complements with translational research, co-authoring papers with unis. Recent stats show Singapore's AI publications up 77% in funding, aiming for top-10 global share by 2030. NAIRD will amplify this, targeting more Nature-index papers.

Boosting Research Publications and Global Impact

As Research Publication News highlights, NAIRD prioritizes high-impact outputs. Prior funding led to leadership in AI ethics papers and engineering citations. RCEs will host workshops, accelerating submissions to CVPR, ACL.

Stakeholders praise the plan: 'It elevates our competitiveness,' per industry experts. Case study: AI Singapore's SEA-LION LLM generated 100+ papers.

Challenges, Risks, and Solutions in AI Advancement

Despite optimism, challenges persist: talent shortages, compute access, ethical risks. NAIRD addresses via GPU clusters, international hires, governance.

• Risks: Model vulnerabilities – Solution: Robustness research.
• Talent gap: Overseas recruitment + local training.
• Compute: National supercomputing expansion.

Balanced views from experts stress multi-stakeholder collaboration for sustainable growth.

Photo by Sraboni Basu on Unsplash

Future Outlook: Singapore's AI Research by 2030

By 2030, NAIRD envisions Singapore as AI leader, with RCEs producing paradigm-shifting papers, 15k experts, sector-wide adoption. Integrated with NAIS 2.0, it promises economic boost via IP commercialization.

For researchers, this means more funding, collaborations. Explore university jobs, postdoc positions, or professor ratings. Singapore's proactive stance offers actionable paths for AI careers.