Indranee Rajah's Vision for AI as a Social Leveller in Singapore's Higher Education Landscape

In a recent post-Budget 2026 discussion, Second Minister for Finance Indranee Rajah articulated a compelling case for artificial intelligence (AI) as a potential force to narrow inequality in Singapore, provided it is rolled out with intention and ethics at its core. Speaking on The Usual Place podcast alongside Singapore Management University (SMU) Assistant Professor of Political Science Nathan Peng and SGTech co-chair Gunasekharan Chellappan, Ms Rajah emphasized that AI could either bridge or widen social divides depending on deployment strategies. This perspective gains added relevance in higher education, where universities like SMU, National University of Singapore (NUS), and Nanyang Technological University (NTU) are pivotal in equipping diverse student cohorts with AI literacy and skills to thrive in an AI-driven economy.

Singapore's higher education institutions are uniquely positioned to democratize AI access. With NUS ranked 8th and NTU 12th in the QS World University Rankings 2026, these universities are not just academic powerhouses but also national engines for inclusive technological advancement. Ms Rajah's comments, made in the context of Budget 2026's $154.7 billion package, underscore the government's commitment to leveraging university-led initiatives to mitigate inequality risks posed by rapid AI adoption.

Budget 2026: Laying the Foundation for Equitable AI Adoption

Singapore's Budget 2026, unveiled by Prime Minister Lawrence Wong on February 12, marks a strategic pivot towards execution in AI governance and deployment. Key announcements include the formation of a National AI Council chaired by the Prime Minister to steer investments and sector-specific AI missions in advanced manufacturing, connectivity, finance, and healthcare. To bolster workforce readiness, participants in selected SkillsFuture courses—starting with accountancy and law—will receive six months of free access to premium AI tools, enabling practical skill-building without financial barriers.

These measures directly intersect with higher education's role. Universities are integrating AI into curricula to ensure graduates from varied socioeconomic backgrounds can harness these tools. For instance, enhancements to schemes like ComLink+—with a new $500 payout for lower-income families—and expanded pre-school subsidies aim to level the playing field early, allowing more children to reach university equipped for AI-era challenges. Ms Rajah noted, "What we have in place are all the building blocks for this. It’s a question of how we can execute better."

SMU's Insights: Bridging AI Accessibility and Ethical Use

SMU has emerged as a frontrunner in addressing AI's dual potential, particularly through the lens of inequality. In January 2026, the university launched the Resilient Workforces Institute (ResWORK), a dedicated research hub partnering with SkillsFuture Singapore to examine AI's effects on skills demand, lifelong learning systems, and workforce resilience. This initiative aligns seamlessly with Budget 2026's emphasis on upskilling, focusing on how AI can empower mid-career workers and fresh graduates alike.

During the podcast, SMU's Prof Nathan Peng highlighted AI's promise in education: tools like generative AI make learning accessible to anyone with a device, potentially closing knowledge gaps. However, he cautioned about a "tinge of inequality," where affluent parents provide superior guidance on AI use, leaving lower-middle-income families at a disadvantage. SMU counters this through programs like the new Master of Science in Business AI, designed to cultivate AI-ready leaders from diverse backgrounds. For students eyeing careers in AI-driven fields, opportunities abound at higher ed jobs platforms tailored for Singapore's academic sector.

University-Led AI Programs Fostering Inclusivity

Singapore's universities are proactively embedding AI literacy across disciplines to reduce inequality. NUS, for example, is advancing AI execution post-Budget 2026, with initiatives like the Unified AI Literacy Framework proposed to standardize programming skills (e.g., Python), critical thinking, and ethical AI projects for all students. NTU complements this with AI-resistant assessments and specialized modules in areas like ammonia engines for sustainable shipping, ensuring practical, equitable applications.

These programs define AI literacy comprehensively: not just technical proficiency but also ethical discernment, echoing Ms Rajah's warning against AI substituting human judgment. Step-by-step curricula start with foundational concepts—explaining neural networks via real-world analogies like pattern recognition in image classification—progressing to hands-on projects. Concrete examples include SMU's cyber defence pioneers merging studies with National Service (NS), where students develop AI models during service, gaining credits towards degrees while contributing to national security.

• SMU Digital Work-Learn Scheme: NSFs pursue info systems degrees while building AI solutions at SAF's AI Centre.
• NUS AI in education: Personalized learning platforms adapting to student needs, reducing dropout risks for underprivileged cohorts.
• NTU eVTOL prototypes: Engineering students from polytechnics gain AI skills via work-learn pathways.

Such integrations ensure no student is left behind, with scholarships and subsidies making access universal. Aspiring academics can find relevant Singapore university jobs to contribute to these efforts.

Challenges: Navigating the Digital Divide in Higher Education

Despite progress, challenges persist. Statistics reveal stark disparities: only 14.5% of SMEs have adopted AI compared to 62.5% of large firms, highlighting a skills gap that universities must bridge. In higher education, lower-middle-income students may lack home support for AI experimentation, as Prof Peng observed. Moreover, individual AI use stands at 58.6% in Singapore—high globally—but age and income gaps remain, with older or lower-income groups lagging.

Cultural context in Singapore amplifies this: meritocratic ethos pressures families to invest in tuition, widening gaps if AI tools become premium. Universities respond with free campus AI labs and peer mentoring, but scaling requires sustained funding. Ms Rajah stressed early intervention: "Attendance is the single largest factor in determining whether a child does well," linking school basics to university success.

Government-University Partnerships: SkillsFuture and Beyond

Budget 2026's free AI tools via SkillsFuture exemplify public-private synergy with universities. SMU's ResWORK collaborates directly, researching AI's workforce impacts to inform policy. NUS and NTU offer micro-credentials aligned with these courses, allowing poly and ITE graduates seamless progression.

Actionable insights include:

• Step 1: Enroll in AI literacy modules at unis for foundational skills.
• Step 2: Apply via work-learn schemes for paid, credit-earning NS experience.
• Step 3: Leverage alumni networks for internships in AI missions.

Real-World Case Studies from Singapore Universities

SMU's NS cyber specialists exemplify success: 3SG Goh Hern Yee, an SMU info systems student, trains AI models deeper than university modules, fulfilling NS while advancing degrees. NTU's sustainability studies with Musim Mas use AI for smallholder farmers, promoting equitable agri-tech. NUS's rain-energy harvesting and ammonia engines demonstrate AI's role in green jobs accessible to all graduates.

Stakeholder views vary: Industry leaders praise accessibility, while unions like NTUC call for retrenchment buffers amid AI disruptions. These cases show universities fostering multi-perspective AI use, with timelines from pilot (2024) to scale (2026).

Future Outlook: AI Ethics and Long-Term Equity

Looking ahead, Singapore's universities aim for AI fluency by 2030 via RIE2025 extensions ($37B quantum/AI investment). Challenges like job redesign—"too early to tell," per Ms Rajah—necessitate agile curricula. Positive outlook: AI creating roles in ethics oversight and human-AI collaboration.

Implications for higher ed: More interdisciplinary programs, diverse faculty hires. Explore university jobs in AI ethics.

Actionable Steps for Students and Educators

To harness AI equitably:

• Audit personal AI skills; enroll in free uni workshops.
• Advocate for inclusive policies via student unions.
• Engage in research at ResWORK or similar.

Photo by Fleur Kaan on Unsplash

Conclusion: Universities as Catalysts for Inclusive AI Growth

Indranee Rajah's endorsement, amplified by SMU insights, positions Singapore's higher education as central to AI-driven equality. By prioritizing access, ethics, and partnerships, universities ensure AI benefits all. Discover opportunities at higher ed jobs, university jobs, career advice, and rate my professor. Singapore's model offers global lessons in thoughtful tech rollout.