Year-long internships to be given to 3,000 tertiary students to counter AI threat to entry-level jobs

A year-long, credit-bearing internship lasts an academic year and can be completed as part of a student’s curriculum before graduation. It matters because students gain deeper workplace experience while still studying, helping close skill gaps created by AI automation.

Unlike a brief internship, this placement is designed like an apprenticeship. Students have time to contribute to substantial projects, learn from experienced colleagues and practise professional judgment. The programme is co-designed by institutes of higher learning and employers.

Polytechnic graduate Pei Joon Yi shows the difference. During his year at NTU’s Lee Kong Chian School of Medicine, he repeatedly applied what he learned while building AI applications. He said the longer experience helped him understand real development processes, improve communication and teamwork, and become more independent. These gains would have been harder during a shorter internship.

Around 3,000 new year-long internships will be offered over the next three years. They are intended for tertiary students and can be completed for academic credit before graduation. The scale reflects concern that students need deeper work experience before entering an AI-affected job market.

The internships were already available to polytechnic and ITE students from 2022 through the TIP Alliance+ programme, led by IMDA. The expansion now includes university students. Placements will be co-designed by institutes of higher learning and employers.

Opportunities will cover industries including technology, finance and healthcare. Previous participating companies include OCBC Bank, Accenture and PSA. IMDA will monitor outcomes closely and consider expanding methods that work. The programme therefore combines wider eligibility with a plan to assess whether year-long placements improve the transition from school to work.

AI automation is making some entry-level roles redundant by handling tasks once assigned to junior employees. The article highlights simple programming, debugging, application testing and system maintenance. As employers increasingly expect new hires to contribute earlier, the first rung of the career ladder may become harder to enter.

Senior Minister of State Tan Kiat How said AI can assist with many junior engineering tasks. These jobs once gave new professionals repeated practice and exposure to real systems. Removing too much of that work can leave graduates with less practical experience, even when employers still need experienced engineers.

The problem is not solved simply by telling graduates to learn more AI. Employers are urged to mentor junior hires deliberately, while schools, industry associations and the Government share responsibility for building the school-to-work bridge. Longer internships are one response to the missing entry-level training.

Longer internships matter because practical judgment grows through repeated decisions, feedback and responsibility. Students can spend enough time understanding a project, contributing to substantial work and seeing how their choices affect real users. This complements classroom knowledge with workplace habits.

Pei Joon Yi’s experience illustrates the mechanism. At NTU’s Lee Kong Chian School of Medicine, he helped build AI applications and learned how to develop web applications around real user needs. He could build on earlier learning with each project instead of starting from scratch. He also developed communication and teamwork skills.

A short placement may end before students understand the full development process or become independent. Pei said this growth would have been harder during a shorter internship. The longer model therefore gives students time to practise technical and interpersonal skills, receive guidance and form professional judgment before graduation.

These internships are created through a shared effort. Institutes of higher learning and employers co-design the placements, so the work can connect academic study with real industry needs. IMDA leads the TIP Alliance+ programme and co-funds hiring costs.

Participating companies can receive up to $1,000 monthly per intern for each eligible year-long internship. Employers involved in earlier runs include OCBC Bank, Accenture and PSA. The internships cover technology, finance, healthcare and other industries, giving students routes into different parts of the economy.

The arrangement reflects Tan Kiat How’s view that no single group can repair the school-to-work bridge alone. Educational institutions, employers, industry associations and the Government all have responsibilities. IMDA will monitor the internships’ outcomes and assess whether successful approaches should be expanded over time. Funding lowers the cost for firms while co-design keeps placements meaningful.

The programme challenges the idea that students should collect as many internships as possible. Tan Kiat How warned that internships should not become an arms race to fill a résumé. The article cites a National University of Singapore internal study linking internship experience with better employment outcomes, but says the benefits eventually diminish.

A substantial placement creates room for deeper contribution. Students can stay with projects longer, understand their users, learn from experienced colleagues and improve their work over time. Pei Joon Yi built on previous learning during his year-long internship instead of starting from scratch, while developing technical and soft skills.

Employers told Tan that quality matters more than quantity. They want to know what a candidate learned, contributed and built, not simply how many placements appear on a résumé. The policy therefore promotes depth and will track outcomes to identify methods worth expanding.

AI automation is the use of artificial intelligence to assist with or perform work previously done by people. In this article, it includes helping with simple programming, debugging code, testing applications and maintaining systems. These tasks are increasingly reducing or changing some entry-level roles.

Those jobs are foundational because beginners learn through doing them. A junior engineer gains practical experience, receives feedback and gradually develops professional judgment. Over time, that learning supports more complex responsibilities. If AI removes every beginner task, graduates may struggle to gain the experience employers expect.

The article says employers still need experienced engineers, but those engineers must begin somewhere. Telling graduates simply to learn more AI will not solve the training gap. Employers are urged to mentor junior hires, while longer internships can provide structured opportunities to practise, contribute and develop the judgment needed for later careers.