NUS Professor Khairudin Aljunied Warns Most Degrees Obsolete by Graduation, Urges AI Skills Focus

In a stark warning to students and educators alike, Associate Professor Khairudin Aljunied from the National University of Singapore (NUS) has declared that most university degrees risk becoming obsolete by the time graduates enter the workforce. Speaking at the Ilmuwan Malaysia Madani forum in Putrajaya, organized by Malaysia's higher education ministry, Aljunied emphasized the rapid pace of technological disruption, particularly driven by artificial intelligence (AI). He urged undergraduates to prioritize developing practical, future-proof skills over traditional academic credentials alone.

Aljunied, a tenured expert in Southeast Asian Islamic and intellectual history within NUS's Department of Malay Studies, highlighted fields across the spectrum—from science, technology, engineering, and mathematics (STEM) to humanities and social sciences—as particularly vulnerable. "The degree that you are earning is not what matters; it's the kind of skills you need to develop," he stated, predicting an even tougher landscape for non-STEM disciplines. His comments resonate deeply in Singapore, where higher education institutions are already racing to integrate AI amid shifting employer demands.

🧠 The Rapid Evolution of Singapore's Job Market

Singapore's graduate employment landscape underscores Aljunied's concerns. The Graduate Employment Survey (GES) 2025, released in early 2026 by the Ministry of Education (MOE), revealed a dip in full-time permanent employment rates for fresh graduates, dropping to around 88-90% within six months across top universities like NUS and Nanyang Technological University (NTU). Median gross monthly salaries held steady at approximately S$4,500-S$4,800, but competition intensified as employers prioritized AI literacy and adaptability.

ManpowerGroup's 2026 Global Talent Shortage Survey identified AI skills as Singapore's hardest-to-fill capability, with nearly one in five job postings referencing AI, machine learning, or generative AI. LinkedIn data shows Gen Z graduates leading job hunts, with 66% planning switches in 2026, driven by AI-fluent roles in finance, tech, and healthcare. Industries like fintech and logistics are tripling entry-level hires for those demonstrating AI proficiency, rewriting job descriptions to emphasize tools over degrees.

Singapore Universities' Proactive AI Integration

NUS is at the forefront, offering a Bachelor of Computing in Artificial Intelligence (Honours) that builds foundational principles in mathematical AI, data-driven learning, and large-scale systems. Students engage in hands-on projects using real datasets, tackling challenges like bias reduction and ethical deployment in areas such as robotics, natural language processing, and computer vision. The programme's flexibility allows double majors or minors in entrepreneurship, preparing graduates for interdisciplinary roles. Complementing this is NUS's MSc in Artificial Intelligence and Innovation, drawing expertise from seven faculties for multidisciplinary AI training. Explore NUS's AI curriculum details here.

NTU mirrors this push with its Bachelor of Computing (Honours) in Artificial Intelligence and Society, blending technical foundations with ethical design and deployment. In 2026, NTU launched eight SkillsFuture Career Transition Programmes (SCTP), including Advanced Professional Certificates in AI Engineering and AI-Powered UX Design. These 3-6 month courses culminate in generative AI capstone projects, targeting mid-career professionals for roles like AI Integration Engineers. NTU's AI training overview.

Singapore Management University (SMU) offers specialized courses like Jump Start in AI, Machine Learning, and Deep Learning, alongside AI for Entrepreneurs, focusing on business applications in finance and strategy. Across these institutions, AI tools are now used for grading, with lecturers at NUS, NTU, SMU, and Singapore University of Technology and Design (SUTD) leveraging them for efficiency while addressing accuracy concerns.

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Government-Led Upskilling: SkillsFuture and Beyond

The Singapore government is bolstering these efforts through Budget 2026 initiatives, including the "Champions of AI" programme for business transformation and enhanced SkillsFuture credits for AI reskilling. The National AI Strategy 2.0 allocates billions for research and training, with S$37 billion in R&D funding. A new Committee for Artificial Intelligence in Higher Education coordinates adoption, ensuring ethical guidelines and collaboration.

Tech undergraduates gain dedicated career support via a job portal for AI, cybersecurity, and data analytics roles. These measures aim to create an AI-bilingual workforce, with 93% of students already using AI for studies, per surveys, though 74% report usage stress—highlighting the need for balanced integration.

Stakeholder Perspectives: Students, Employers, and Educators

Students echo Aljunied's call; many push for curriculum tweaks, as he advised: inform deans and vice-chancellors of needs like video production and graphic design alongside AI. Employers, per Indeed's Work Ahead report, value practical AI application over credentials, with half of vacancies being new AI-driven roles.

Educators at NUS forums debate AI's role, from hype to hope, emphasizing primary thinking amid convenience. A response from Malaysian academic P. Ramasamy critiqued Aljunied, arguing education transcends utility, but Singapore's pragmatic approach prioritizes employability.

Case Studies: Success Stories from Singapore Campuses

At NUS, Acacia Residential College's AI-themed programme features hackathons and societal impact discussions, producing graduates contributing to industry research. NTU's capstone projects have led to AI apps deployed in real-world settings, enhancing portfolios.

SMU's AI/ML courses have upskilled professionals, with alumni in high-demand fintech roles. These examples show hybrid curricula—blending theory, ethics, and practice—yielding 90%+ employability rates despite market tightness.

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Challenges and Ethical Considerations

• Data Bias and Reliability: AI systems require high-quality data; students learn mitigation techniques.
• Job Displacement Fears: While AI automates routine tasks, it creates roles needing human oversight.
• Equity Gaps: Ensuring access for all, via subsidies and modular learning.
• Academic Integrity: Low AI cheating reports, but policies evolve with detectors.

Future Outlook: Hybrid Degrees and Lifelong Learning

By 2030, Singapore aims for widespread AI literacy, with universities evolving to micro-credentials and stackable qualifications. Aljunied's warning catalyzes this shift, positioning Singapore's higher education as a global model. Graduates mastering AI alongside soft skills like critical thinking will thrive, turning obsolescence into opportunity.

For aspiring students, explore programmes at Singapore university jobs or career advice resources to align studies with market needs.