SINGAPORE: When DBS Group announced in February that artificial intelligence (AI) could cut up to 4,000 contract and temporary jobs at the bank over the next few years, it spotlighted a growing concern.
Across industries from marketing to finance to software, AI is automating the “ground floor” of careers – the very roles used to teach workers the ropes.
Careers are not downloaded fully formed; they are built through hands-on experience, structured learning and mentorship – a foundation that’s rapidly eroding.
Junior employees have traditionally learnt by doing foundational work. Writers edited press releases. Designers created social media graphics. Programmers fixed bugs and wrote tests. Learning was embedded in the job itself.
Today, companies increasingly use ChatGPT to draft content, Midjourney to design visuals, and GitHub Copilot to generate code. While impressive, these tools are also removing crucial learning opportunities.
A 2023 ResumeBuilder survey found that 37 per cent of US companies had already replaced workers with ChatGPT, and 44 per cent were planning more replacements. AI could automate 25 per cent of current work tasks globally, affecting 300 million jobs, reported Goldman Sachs the same year.
The Monetary Authority of Singapore in 2019 projected that one in three finance jobs in Singapore alone could be transformed or eliminated by automation.
AI-generated work often appears polished but may lack the technical or critical depth of human judgment and expertise. Without foundational training, junior employees risk becoming dependent on tools they cannot truly assess or evaluate.
Research from MIT and Stanford shows AI-assisted workers complete tasks 40 per cent faster – but their work often requires more revision by seniors.
A copywriter using ChatGPT might not understand why one tagline lands while another falls flat. A developer relying on code generators may be lost when systems break in ways the AI is unable to foresee or account for.
This creates a dangerous illusion: the work is completed faster and largely looks good, but true competence and understanding are missing. If entry-level roles become performative – driven by prompting rather than critical thinking – we risk building a future where nobody truly knows how things work.
Besides technical competence, the disappearance of entry-level jobs threatens the development of critical thinking and nuanced judgment.
Entry-level positions traditionally allow young professionals to understand company culture, learn from making mistakes in relatively low-stakes scenarios, and develop soft skills such as communication, collaboration, and resilience.
These soft skills – critical for future leadership – cannot be automated. Yet, without junior roles that explicitly teach and nurture these abilities, the next generation risks entering senior positions technically capable but lacking essential interpersonal and strategic skills.
This shift particularly affects students and young workers from less privileged backgrounds.
Previously, on-the-job training helped level the playing field. However, if entry-level positions now demand pre-existing expertise without offering learning opportunities, those without industry connections face significant barriers.
We are already seeing this play out in rising unpaid internships and portfolio expectations. According to a 2024 National Youth Council survey, 68 per cent of young job seekers in Singapore reported that internship experience is now considered "essential" rather than "preferred" for entry-level positions.
When only those who can "fake it" with AI tools or secure mentorship through personal networks are considered hireable, we narrow both the diversity and depth of future talent.
Singapore could consider responding by launching a national apprenticeship scheme – building on the SGUnited Traineeships programme from COVID-19, but retooled for the AI age.
Such a scheme could:
• Offer 12–24 month paid placements for fresh graduates, polytechnic and ITE students
• Emphasise AI-augmented work with real mentorship
• Include structured feedback, not just key performance indicators to hit
• Encourage mentorship from senior employees explicitly, recognising and rewarding their role in shaping future talent.
Countries with similar programmes have seen promising outcomes. Germany’s dual-track system keeps youth unemployment at 5.7 per cent – well below the European Union average of 14.5 per cent.
Singapore’s SkillsFuture Earn and Learn scheme boasts a 93 per cent job placement rate in technical fields. It is time to extend this success to knowledge work too.
However, unlike the SG Traineeships programme, this cannot be a temporary patch. AI isn’t a crisis to outlast – it’s a shift to outsmart. We need new systems to grow talent in a world where doing the task is not always how you learn it anymore.
This is not about Gen Z being “lazy” or a lack of talent. It’s about a system that’s no longer structured to produce mastery. Apprenticeships are not a nostalgic idea; they are a practical response.
Research across various industries shows that many seniors are willing to mentor, but cannot do so without structure. If we can build apprenticeship into our workflows, we strengthen learning and loyalty for both senior and junior workers.
Companies also benefit from higher-quality talent pipelines, and employees from gaining valuable, marketable skills.
Governments, educational institutions and private companies must collaborate to establish frameworks that institutionalise learning in the age of AI. Curriculum updates should integrate AI literacy alongside human judgment, ethics, and creativity, preparing students not just to leverage AI but to question and guide its responsible use.
For decades, Singapore has thrived on a shared, unspoken promise: work hard, play by the rules, and you’ll be rewarded. Our success has never been just about gross domestic product. It was about building trust – between citizen and state, worker and employer.
This has made Singapore one of the world's safest, most developed nations despite our lack of natural resources. It explains our reliable public transport, clean streets, and globally competitive schools.
Should young Singaporeans lose faith in the social contract that promises effort will lead to growth and reward, our collective trust will erode.
If AI is here to stay – and it is – we must ensure human judgment, mentorship, and mastery remain integral to our workforce. This approach safeguards not just our economy but our identity as a society committed to advancement for all.
This isn’t charity. It’s a long-term investment in capability. No matter how powerful the tools in our kit become, we still need to know how – and when – to use them well.
It starts with someone willing to teach – and someone given a real chance to learn.
Darwin Gosal is a product manager in Singapore’s public sector and a former tech startup founder. He writes about technology, science, and global trends.
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Across industries from marketing to finance to software, AI is automating the “ground floor” of careers – the very roles used to teach workers the ropes.
THE VANISHING GROUND FLOOR
Careers are not downloaded fully formed; they are built through hands-on experience, structured learning and mentorship – a foundation that’s rapidly eroding.
Junior employees have traditionally learnt by doing foundational work. Writers edited press releases. Designers created social media graphics. Programmers fixed bugs and wrote tests. Learning was embedded in the job itself.
Today, companies increasingly use ChatGPT to draft content, Midjourney to design visuals, and GitHub Copilot to generate code. While impressive, these tools are also removing crucial learning opportunities.
A 2023 ResumeBuilder survey found that 37 per cent of US companies had already replaced workers with ChatGPT, and 44 per cent were planning more replacements. AI could automate 25 per cent of current work tasks globally, affecting 300 million jobs, reported Goldman Sachs the same year.
The Monetary Authority of Singapore in 2019 projected that one in three finance jobs in Singapore alone could be transformed or eliminated by automation.
THE COMPETENCE GAP
AI-generated work often appears polished but may lack the technical or critical depth of human judgment and expertise. Without foundational training, junior employees risk becoming dependent on tools they cannot truly assess or evaluate.
Research from MIT and Stanford shows AI-assisted workers complete tasks 40 per cent faster – but their work often requires more revision by seniors.
A copywriter using ChatGPT might not understand why one tagline lands while another falls flat. A developer relying on code generators may be lost when systems break in ways the AI is unable to foresee or account for.
This creates a dangerous illusion: the work is completed faster and largely looks good, but true competence and understanding are missing. If entry-level roles become performative – driven by prompting rather than critical thinking – we risk building a future where nobody truly knows how things work.
LOSING HUMAN JUDGMENT
Besides technical competence, the disappearance of entry-level jobs threatens the development of critical thinking and nuanced judgment.
Entry-level positions traditionally allow young professionals to understand company culture, learn from making mistakes in relatively low-stakes scenarios, and develop soft skills such as communication, collaboration, and resilience.
These soft skills – critical for future leadership – cannot be automated. Yet, without junior roles that explicitly teach and nurture these abilities, the next generation risks entering senior positions technically capable but lacking essential interpersonal and strategic skills.
Related:
THE EQUITY CHALLENGE
This shift particularly affects students and young workers from less privileged backgrounds.
Previously, on-the-job training helped level the playing field. However, if entry-level positions now demand pre-existing expertise without offering learning opportunities, those without industry connections face significant barriers.
We are already seeing this play out in rising unpaid internships and portfolio expectations. According to a 2024 National Youth Council survey, 68 per cent of young job seekers in Singapore reported that internship experience is now considered "essential" rather than "preferred" for entry-level positions.
When only those who can "fake it" with AI tools or secure mentorship through personal networks are considered hireable, we narrow both the diversity and depth of future talent.
A STRUCTURED SOLUTION
Singapore could consider responding by launching a national apprenticeship scheme – building on the SGUnited Traineeships programme from COVID-19, but retooled for the AI age.
Such a scheme could:
• Offer 12–24 month paid placements for fresh graduates, polytechnic and ITE students
• Emphasise AI-augmented work with real mentorship
• Include structured feedback, not just key performance indicators to hit
• Encourage mentorship from senior employees explicitly, recognising and rewarding their role in shaping future talent.
Countries with similar programmes have seen promising outcomes. Germany’s dual-track system keeps youth unemployment at 5.7 per cent – well below the European Union average of 14.5 per cent.
Singapore’s SkillsFuture Earn and Learn scheme boasts a 93 per cent job placement rate in technical fields. It is time to extend this success to knowledge work too.
BUILDING LONG-TERM INFRASTRUCTURE
However, unlike the SG Traineeships programme, this cannot be a temporary patch. AI isn’t a crisis to outlast – it’s a shift to outsmart. We need new systems to grow talent in a world where doing the task is not always how you learn it anymore.
This is not about Gen Z being “lazy” or a lack of talent. It’s about a system that’s no longer structured to produce mastery. Apprenticeships are not a nostalgic idea; they are a practical response.
Research across various industries shows that many seniors are willing to mentor, but cannot do so without structure. If we can build apprenticeship into our workflows, we strengthen learning and loyalty for both senior and junior workers.
Companies also benefit from higher-quality talent pipelines, and employees from gaining valuable, marketable skills.
Governments, educational institutions and private companies must collaborate to establish frameworks that institutionalise learning in the age of AI. Curriculum updates should integrate AI literacy alongside human judgment, ethics, and creativity, preparing students not just to leverage AI but to question and guide its responsible use.
Related:
SINGAPORE'S STRATEGIC OPPORTUNITY
For decades, Singapore has thrived on a shared, unspoken promise: work hard, play by the rules, and you’ll be rewarded. Our success has never been just about gross domestic product. It was about building trust – between citizen and state, worker and employer.
This has made Singapore one of the world's safest, most developed nations despite our lack of natural resources. It explains our reliable public transport, clean streets, and globally competitive schools.
Should young Singaporeans lose faith in the social contract that promises effort will lead to growth and reward, our collective trust will erode.
If AI is here to stay – and it is – we must ensure human judgment, mentorship, and mastery remain integral to our workforce. This approach safeguards not just our economy but our identity as a society committed to advancement for all.
This isn’t charity. It’s a long-term investment in capability. No matter how powerful the tools in our kit become, we still need to know how – and when – to use them well.
It starts with someone willing to teach – and someone given a real chance to learn.
Darwin Gosal is a product manager in Singapore’s public sector and a former tech startup founder. He writes about technology, science, and global trends.
Continue reading...