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When the Young Workers Run Out: Aging, Automation and the Question of Who Benefits
A nation’s wealth is only as secure as its plan for who will do the work.
Consider a fictional machining firm in Singapore’s western industrial estates, which we’ll call Fictitious Precision. It makes components for medical devices and aircraft. For most of its history, the thing that held it back was orders. Today it is people.
Its production supervisor, Madam Lim, is sixty-three and has spent thirty-one years on the shop floor. She is the only person who truly understands the temperament of the oldest milling line. Two of her senior technicians will retire within eighteen months. Each of three recruitment drives has drawn fewer applicants than the last, and most of those who come would rather work in an office than on a factory floor.
The firm is invented. Its dilemma is not. Across advanced economies, and increasingly in middle-income ones, the scarcest input is no longer capital or land. It is working-age people.
The arithmetic behind the headache
Singapore shows how quickly this shift can unfold. Official figures show that citizens aged 65 and above rose from 13.1 per cent of the citizen population in 2015 to 20.7 per cent in June 2025. That share is projected to reach roughly one in four by 2030. Over the same decade, the number of citizens aged 80 and above grew from about 91,000 to 145,000. Meanwhile, the resident total fertility rate stood at 0.97 in 2024, less than half the replacement level of 2.1.
These numbers partly reflect success. Good healthcare, decent housing and public safety lengthen lives. But longevity is ultimately financed by people in work. As the ratio of workers to retirees narrows, each worker carries a heavier load.
Japan is further along the same road. Government estimates released in September 2026 put people aged 65 and over at 29.6 per cent of the population. That is the highest share among the 39 countries with populations of 40 million or more, and it is projected to approach 35 per cent by 2040. Japan has leaned heavily on longer working lives. In 2025, a record 9.43 million workers were 65 or older, about 13.8 per cent of all workers.
South Korea shows how fast the change can arrive. Its fertility rate fell to 0.72 in 2023, the world’s lowest, before recovering to 0.80 in 2025. The rebound is welcome, but it is still below 40 per cent of replacement level. Babies born today will not enter the workforce until the 2040s.
A global story, not a local one
This is not an East Asian peculiarity. The United Nations projects that world population will peak at around 10.3 billion in the mid-2080s. Population has already peaked in sixty-three countries, which together hold more than a quarter of humanity. By the late 2070s, people aged 65 and over are expected to outnumber children under 18. East Asia is simply first in line, and its choices may well become the template others follow.
Four pressure points
An aging workforce does not press on an economy evenly.
Labour-intensive sectors feel it first. Construction, manufacturing, logistics, cleaning and food services all depend on physical shift work, which younger and better-educated citizens increasingly decline.
Demand for care rises just as carers become scarce. Older populations need more nurses, therapists and home helpers. They need them precisely when fewer people are willing to do care work that is demanding and modestly paid.
Public finances tighten. Pensions, healthcare and long-term care are funded largely from the earnings of people in work. A narrower base of workers and a growing number of beneficiaries leave governments with uncomfortable choices.
Experience walks out of the door. When Madam Lim retires, Fictitious loses more than a pair of hands. It loses three decades of judgement about machines, suppliers and customers. Multiply that across millions of retirements, and the loss of institutional memory becomes an economic force in its own right.
Why familiar answers fall short
Governments have pursued three main responses. Birth incentives help families, and Korea’s uptick suggests they are not wasted. But they work slowly, and no wealthy country has restored fertility to replacement level. Immigration keeps many Asian economies running. Yet it raises real questions of social cohesion and infrastructure, and it draws on source countries that are themselves beginning to age. Longer working lives make a genuine difference, as Japan shows, but bodies tire and not every job suits a seventy-year-old.
Each answer buys time. None changes the underlying arithmetic.
The fourth answer: a new kind of workforce
The fourth answer is to change what a worker is. That means multiplying the productivity of the people we have and handing suitable work to machines. The United Nations itself encourages aging societies to use technology to raise productivity at every age.
This is already happening. The International Federation of Robotics reports the following figures for 2024:
South Korea operated 1,220 industrial robots per 10,000 manufacturing employees, the highest density in the world.
Singapore was second at 818, and its robot density has grown about 13 per cent a year since 2019.
Japan was fourth at 446 and remains the world’s leading producer of robots.
The global average was 132.
It is tempting to read this as demography alone driving automation. A more careful reading treats labour scarcity as one powerful driver among several. Industrial structure matters too, especially electronics and automotive manufacturing, and so does deliberate national policy. The pattern is striking, but correlation is not the whole story.
At Fictitious, the shift began modestly. The company installed two collaborative robots, or cobots, which are designed to work safely beside people rather than behind cages. The cobots took over loading raw stock and unloading finished parts on the oldest line. The retiring technicians were not replaced by new hires. Instead, one younger technician learned to supervise both cobots, while Madam Lim spent her final working years teaching the judgement no machine yet has. Output rose and overtime fell. The production schedule began to follow customer orders rather than attendance.
Where AI enters, and where governance must follow
Robots address the physical gap. AI increasingly addresses the cognitive one, in at least three ways.
Predictive workforce planning combines retirement dates, staffing history and order forecasts. It can show years in advance where skills gaps will open.
Retrieval-augmented generation lets an AI system answer questions by drawing on a firm’s own documents. A veteran’s notes, maintenance logs and recorded explanations become searchable guidance. A new technician’s questions are then answered from the firm’s own experience rather than from generic internet text.
Agentic AI can now complete multi-step administrative tasks under defined rules. Examples include scheduling, procurement follow-up and compliance reporting.
None of these tools should run unsupervised. The strongest deployments keep a named person accountable for each consequential decision, with AI proposing and humans approving. This reflects established practice, such as Singapore’s Model AI Governance Framework and the ISO/IEC 42001 standard for AI management systems. Machines can multiply human effort. They should not replace human responsibility.
The question this leaves open
For two centuries, each generation of workers handed the baton to a larger generation behind it. That relay has changed, because the next runner is smaller. Machines cannot run the race for us, but they can carry part of the load between handovers.
That brings us back to Fictitious’s milling line. Output is up, costs are down and profits will rise. Who benefits?
Suppose the gains flow only to the owners. The younger technician gains a little, the retirees gain nothing, and the community sees a factory that produces more while employing fewer people. Repeat that across an economy, and a nation becomes richer on paper but more divided in practice.
Now suppose some of the gains are shared. They could go to fair wages, investment in skills, contributions that support the elderly, and care for the environment. Then the robot on the milling line becomes part of a national strategy for shared prosperity.
Machines can fill the gap left by missing workers. Whether they also narrow the gap between rich and poor depends on choices that people, not machines, must make. That is the question this series sets out to explore.
References
National Population and Talent Division, Prime Minister’s Office, Singapore. . September 2025.
United Nations DESA, Population Division. . July 2024.
International Federation of Robotics. (World Robotics 2025 data). 8 April 2026.
Jiji Press via Nippon.com. 20 September 2026.
The Korea Times (Yonhap). 26 August 2026.
Infocomm Media Development Authority / PDPC Singapore. Model AI Governance Framework (insert URL after checking).
ISO/IEC 42001:2023, Information technology — Artificial intelligence — Management system (insert iso.org URL after checking).
Disclaimers
AI-assistance disclaimer
This article was prepared with the assistance of artificial intelligence tools for research support, drafting and editing. All content, analysis and conclusions were reviewed, verified and approved by the author, who takes full responsibility for the final text.
Author’s disclaimer
The views expressed in this article are the author’s personal opinions. They are provided for general educational and thought-leadership purposes only. They do not constitute financial, investment, legal, employment or other professional advice and should not be relied on as such. Fictitious Precision and all individuals in it are fictional composites. Any resemblance to actual companies or persons is coincidental. Statistics are drawn from the public sources cited and were believed accurate at the time of writing. Projections are inherently uncertain, and source figures may be revised. References to organisations, standards and frameworks do not imply endorsement by or affiliation with them. Readers should seek independent professional advice before making decisions based on this content. Publication on LinkedIn or by the World Certified Institute does not imply that either platform endorses the views expressed. The author accepts no liability for any loss arising from reliance on this article.
Disclaimer: This illustration was collaboratively generated using AI imagery tools (Gemini by Google). It is an original, conceptual artwork designed for editorial accompaniment and does not depict real individuals, actual corporate facilities, or specific branded machinery.
This article was written by Dr John Ho, a professor of management research at the World Certification Institute (WCI). He has more than 4 decades of experience in technology and business management and has authored 28 books. Prof Ho holds a doctorate degree in Business Administration from Fairfax University (USA), and an MBA from Brunel University (UK). He is a Fellow of the Association of Chartered Certified Accountants (ACCA) as well as the Chartered Institute of Management Accountants (CIMA, UK). He is also a World Certified Master Professional (WCMP) and a Fellow at the World Certification Institute (FWCI).
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World Certification Institute (WCI) is a global certifying and accrediting body that grants credential awards to individuals as well as accredits courses of organizations.
During the late 90s, several business leaders and eminent professors in the developed economies gathered to discuss the impact of globalization on occupational competence. The ad-hoc group met in Vienna and discussed the need to establish a global organization to accredit the skills and experiences of the workforce, so that they can be globally recognized as being competent in a specified field. A Task Group was formed in October 1999 and comprised eminent professors from the United States, United Kingdom, Germany, France, Canada, Australia, Spain, Netherlands, Sweden, and Singapore.
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