By Michael Fung
For more than two centuries, the university degree has been the gold standard of human capital development. It opened doors to careers, signaled competence to employers, and promised upward social mobility. But that social contract is beginning to crack.
Artificial intelligence is not simply changing how we work — it is changing how quickly work changes. New skills emerge and existing ones become obsolete in months, and entire occupations are being redefined faster than universities can redesign their curricula. Meanwhile, forward-thinking employers are discovering that possessing the right skills often matters far more than possessing the right diploma.
The degree is not disappearing. But its monopoly over talent recognition is.
The challenge confronting governments, businesses, and universities is no longer whether we need new models of learning, but whether our institutions can adapt at the pace of innovation.
AI has exposed a weakness that already existed
Much of today’s debate focuses on AI replacing jobs. That is the wrong debate. The real disruption lies in the accelerating mismatch between education and employment.
Across virtually every sector — from manufacturing and finance to healthcare and software development — skills requirements are evolving at unprecedented speed. Generative AI has already elevated demand for capabilities such as prompt engineering, AI-assisted workflows, data literacy, and human-AI collaboration, while simultaneously reshaping countless existing roles.
Yet universities typically require several years to design, approve, accredit, and launch new programmes. By the time graduates enter the workforce, their accumulated knowledge often lags behind current demands.
This is not a failure of universities per se. It is the consequence of institutions built for stability operating in a dynamic environment buffeted by constant disruption.
The future belongs to learning not degrees
The industrial economy rewarded educational milestones. The knowledge economy rewards continuous learning.
Increasingly, careers will require multiple episodes of reskilling and upskilling, rather than a single university education followed by a lifetime of employment. Individuals will develop portfolios of capabilities acquired through multiple sources — universities, employers, online platforms, professional certifications, and workplace experience.
This is why digital credentials and micro-credentials are attracting growing attention.
Unlike traditional transcripts, digital credentials capture specific competencies, verify demonstrated skills, and remain portable throughout a lifetime. They enable learning to become modular, stackable, and continuously updated, providing a vital infrastructure for lifelong learning.
The challenge of building a common skills language
My previous work leading the SkillsFuture movement fundamentally changed the conversation about workforce development in Singapore. The success of the initiative did not stem simply from offering more courses; it came from creating a common national language for skills — shared competency frameworks, recognised occupational standards, and trusted credentials understood by workers, employers, and education providers alike.
That lesson stayed with me.
In my recent endeavours spanning Latin America and Africa, engaging with governments, companies, and institutions to build skills for industrial sectors, I repeatedly encounter the same problem.
Governments launch workforce programmes. Universities develop micro-credentials. Technology companies build sophisticated learning platforms. Employers invest in corporate academies. Yet too often, these remain isolated islands of innovation.
Without common standards, interoperable credentials, and coordinated governance, innovation rarely scales.
The obstacle is not technology. It is fragmentation.
AI can finally make skills visible
Ironically, the same technology disrupting labour markets may also provide the solution.
Artificial intelligence now enables us to analyse millions of job postings in real time, identify emerging skills, and forecast changing workforce needs in near real-time, months or even years before conventional labour market surveys detect them.
Instead of reacting to yesterday’s shortages, governments can anticipate tomorrow’s opportunities. Instead of redesigning curricula every five years, universities can continuously update learning pathways. Instead of hiring based primarily on degrees, employers can increasingly recruit based on demonstrated competencies.
AI allows us to move from labour-market information to genuine skills intelligence.
Building ecosystems, not isolated programmes
However, forecasting is only the beginning. The greater challenge is to connect every part of the system.
Governments, employers, universities, technology providers, industry associations, and civil society must operate as a coordinated skills ecosystem rather than as disconnected entities pursuing independent agendas.
This philosophy underpins the Skills Ecosystems initiative at the Institute for the Future of Education. We are working across multiple Latin American countries —including Mexico, Chile, and Colombia — to align skills forecasting, modular learning pathways, digital credentialing, employer recognition, and workforce deployment into a coherent ecosystem that serves both economic competitiveness and social inclusion.
The objective is not simply to issue more credentials. It is to help people navigate a lifetime of transitions between learning and work.
The next competitive advantage
Countries traditionally competed to attract investment through infrastructure, tax incentives, and industrial policy. Increasingly, they will compete on something far more fundamental: how effectively and nimbly they develop, recognise, and redeploy human talent.
The winners will not necessarily be those with the most prestigious universities. They will be those capable of building agile skills ecosystems where education, industry, and technology evolve in tandem.
The implications extend well beyond economic growth.
When learning acquired in workplaces, communities, and online platforms is widely recognised alongside formal education, opportunities expand for millions of people. Workers gain new pathways into better jobs, employers access broader talent pools, and societies become more resilient in the face of disruption.
This is why the debate should never be framed as degrees versus digital credentials.
Degrees will remain indispensable for deep disciplinary knowledge. But in an AI-driven economy, they are only the beginning of the story — not the entire story.
The future belongs to societies that recognise learning wherever it happens and enable people to keep learning throughout their lives. This lesson does not apply only to Singapore and Latin America; it is equally relevant across Asia and the rest of the world.
Looking ahead, the most valuable credential may no longer be just the degree on the wall, but the demonstrated capability to learn, adapt, and thrive in a world where change has become the only constant.
Michael Fung is the Director, Institute for the Future of Education at Tecnológico de Monterrey, Mexico.
DISCLAIMER: The views expressed are solely of the author and ETEDUCATION does not necessarily subscribe to it. ETEDUCATION will not be responsible for any damage caused to any person or organisation directly or indirectly.
