For a long time, the contract seemed relatively simple. People studied for fifteen or twenty years, learned a profession, and then relied on much of that knowledge for several decades. A degree marked the transition into professional life and, in developed economies as well as in many emerging countries, became one of the principal instruments of social mobility.

That model has not disappeared. But the economic environment on which it rested is changing.

Artificial intelligence is now automating certain intellectual tasks. The energy transition is creating new industrial skills. Demographic ageing is reshaping the needs of several economies. Geopolitical fragmentation is reorganizing production chains. Digital technologies allow some activities to overcome geographical constraints, while automation continues to advance across industry.

Work is changing, but something deeper is changing with it: the speed at which skills become insufficient.

According to the World Economic Forum’s Future of Jobs Report 2025, surveyed employers estimate that 39% of workers’ core skills will be transformed or become outdated between 2025 and 2030. At the same time, the International Labour Organization estimates that one in four workers worldwide is already employed in an occupation with some degree of exposure to generative artificial intelligence.

The question of the twenty-first century is therefore no longer simply how many people need to be educated.

It is how to prepare individuals for an economy in which learning no longer necessarily precedes work, but increasingly becomes a permanent part of it.

Education has always followed the economy

Education has never evolved independently of the productive system.

In agricultural societies, most skills required for production were transmitted within families, communities and guilds. People learned by observing, repeating and gradually mastering the practices of a trade.

The Industrial Revolution profoundly altered this organization. Factories and, later, large corporations needed populations capable of reading, writing, calculating, following schedules and operating within standardized production systems. The expansion of primary and then secondary education accompanied this economic transformation just as much as it represented social progress.

The twentieth century brought another shift. The expansion of services, public administration, engineering, finance, medicine and technologically more complex industries gave higher education a central economic function. Degrees gradually became passports to certain professions, but also to social mobility.

From the 1980s onward, the expansion of the knowledge economy reinforced this dynamic. Information, research, software, intellectual property and innovation occupied an increasingly important place in value creation.

One assumption nevertheless remained largely intact: a substantial share of the knowledge acquired early in life would remain useful throughout much of a professional career.

It is this assumption that is now becoming far more fragile.

The profession remains, the tasks change

Artificial intelligence provides perhaps the clearest illustration of this rupture.

The question is often framed dramatically: how many jobs will machines eliminate? Recent work by the International Labour Organization suggests a more nuanced interpretation.

In 2025, the ILO and Poland’s NASK research institute assessed nearly 30,000 occupational tasks to measure their exposure to generative artificial intelligence. Their conclusion is significant: roughly one in four workers worldwide is employed in an occupation with some degree of exposure to these technologies, but job transformation currently appears more likely than outright job disappearance.

The distinction matters.

An accountant may remain necessary even as parts of data entry, reconciliation, document verification or preliminary analysis become automated. A lawyer may remain indispensable even as legal research and initial contract drafts are produced by AI systems. An engineer may retain responsibility for a design while certain calculations, simulations or preparatory tasks are accelerated by software.

The unit of transformation, therefore, is not always the profession.

It is often the task.

This helps explain why automation is now affecting occupations that once appeared relatively protected by their level of qualification. The ILO has notably observed increasing exposure in some highly digitized technical professions, including financial analysts, software developers, programmers and investment advisers.

Artificial intelligence no longer simply divides manual from intellectual work.

It is progressively moving through both.

The degree is not disappearing

This transformation does not mean that academic degrees are becoming irrelevant.

They continue to signal academic achievement, learning capacity and mastery of a discipline and, in regulated professions, remain indispensable qualifications. Universities also remain centers of research, scientific transmission and intellectual formation that cannot simply be replaced by professional certifications.

But the function of the degree is changing.

It is becoming less a definitive certification of skills than the first foundation on which additional learning will have to be built.

This shift is already visible in recruitment practices. The Future of Jobs Report 2025 indicates that professional experience remains the most widely used mechanism for assessing candidates among surveyed companies. Direct skills assessments are also gaining importance, while some organizations are developing recruitment approaches increasingly based on demonstrated capabilities.

Degrees therefore remain important, but they increasingly share their role with experience, certifications, digital capabilities, professional achievements and the ability to learn quickly.

Learning becomes part of work

The logical consequence is considerable.

Education can no longer be concentrated almost exclusively within the first twenty or twenty-five years of life.

Based on its survey of more than 1,000 major employers representing over 14 million workers, the World Economic Forum estimates that 59 out of every 100 workers will require some form of additional training by 2030. Of these, 29 could be upskilled within their existing roles and 19 could be retrained and redeployed elsewhere within their organizations. Eleven, however, risk not receiving the training they need.

That final category reveals one of the central challenges of the current transformation.

Continuous training is becoming both an instrument of competitiveness and a mechanism of protection against professional exclusion.

The OECD similarly emphasizes that learning can no longer end with the acquisition of a degree. Workplace training, professional development, reskilling, adult education and second-chance programs are increasingly different components of the same skills-development system.

The boundary between education and work is therefore becoming more porous. People no longer learn only before entering a company. They learn while working because tools, processes and sometimes the profession itself continue to evolve.

The company enters the classroom

This evolution is also changing the traditional distribution of responsibilities.

For a long time, educational institutions trained people and companies employed them. That separation is becoming less distinct.

Large organizations are developing their own corporate universities, learning platforms, certification programs and reskilling pathways. Technology companies offer professional certifications. Digital platforms make it possible to acquire specific skills within weeks or months. Micro-credentials increasingly complement traditional academic programs.

Training consequently becomes a productive investment.

According to the World Economic Forum survey, 85% of employers expect to prioritize workforce upskilling in response to transformations anticipated through 2030. Skills gaps are also the most frequently cited obstacle to business transformation among surveyed employers.

Human capital is therefore joining technology, infrastructure, energy and data among the decisive factors of competitiveness.

A company may possess capital and sophisticated technologies yet face a constraint that is much harder to overcome: an inability to find people capable of using them effectively.

Artificial intelligence enters the classroom too

The technology transforming work is simultaneously transforming the way people learn.

Conversational assistants can explain concepts, translate texts, generate exercises, review certain types of work or adapt explanations to a student’s level. Platforms can personalize learning pathways. Language barriers can be reduced. Access to certain forms of knowledge becomes almost instantaneous.

But this abundance creates a paradox.

When producing an answer becomes easy, knowing how to evaluate that answer becomes more important.

UNESCO has therefore emphasized a human-centered approach to artificial intelligence in education and the development of skills enabling learners to use these technologies responsibly and critically.

This gradually shifts the function of education.

Memorization remains necessary. It is impossible to analyze a field properly without understanding its fundamental concepts. But the relative value of other abilities increases: defining a problem, verifying information, distinguishing correlation from causation, understanding the limitations of a model, comparing sources, interpreting results and exercising judgment.

Schools therefore do not simply need to teach students how to use artificial intelligence.

They need to teach them how to think in an environment where artificial intelligence is ubiquitous.

Human skills change in value

This shift can also be seen in employers’ expectations.

Artificial intelligence and data processing are among the skills expected to grow most rapidly in importance through 2030, according to employers surveyed by the World Economic Forum. But technological skills alone are not enough.

Analytical thinking remains the most frequently cited core skill. Creativity, resilience, flexibility, adaptability, leadership and curiosity also appear among the capabilities regarded as important or increasing in significance.

There is no contradiction here.

The more machines become capable of producing, classifying and analyzing information, the more certain human functions shift toward what surrounds that information: identifying the right question, understanding context, choosing between competing possibilities, taking responsibility for decisions, communicating, negotiating and interpreting consequences.

Technology does not necessarily diminish the value of human skills.

It changes their hierarchy.

A new educational divide

This transformation nevertheless contains a major risk.

Not everyone has the same capacity to retrain.

Highly qualified workers often have better access to professional training, digital technologies and mobility opportunities. Large companies can finance reskilling programs that smaller organizations cannot always provide. Economies with strong universities, digital infrastructure and effective vocational training systems begin with a considerable advantage.

The OECD has documented precisely this inequality in participation in adult learning. People who may have the greatest need for retraining — low-skilled workers, employees in declining sectors or adults with limited initial qualifications — often face the greatest obstacles to accessing it.

The paradox is severe.

Those whose skills are most vulnerable to obsolescence may also have the fewest resources with which to acquire new ones.

Lifelong learning therefore becomes a matter of social cohesion as much as economic competitiveness.

Education becomes an instrument of power

The same logic operates at the level of states.

International competition is no longer limited to access to natural resources, markets or industrial capacity. It increasingly concerns the ability to produce, attract and retain engineers, scientists, researchers, entrepreneurs and specialists in advanced technologies.

Universities consequently participate directly in economic power. Laboratories feed technological ecosystems. Immigration systems partly determine the international circulation of talent. Investment in research contributes to scientific and industrial sovereignty.

In an economy where knowledge evolves rapidly, the quality of an education system can therefore no longer be measured solely by the number of graduates it produces.

It also depends on its ability to allow an entire population to continue learning.

Education can no longer prepare people for a static world

Every major economic transformation has eventually transformed education.

Industrialization contributed to the expansion of mass schooling. The knowledge economy encouraged the growth of higher education. The age of artificial intelligence may require a third transformation: the emergence of a system in which education is no longer primarily a period of life, but an infrastructure accompanying the entire professional lifespan.

The change goes deeper than simply modernizing school curricula.

It changes the definition of what it means to be qualified.

Under the old model, being qualified essentially meant possessing the knowledge required to perform a profession. Under the new one, it also means being capable of renewing that knowledge when the profession changes.

The real educational advantage may therefore no longer be knowing more than others at a particular moment.

It may be remaining capable of learning when what we already know is no longer enough.

Main Sources

International Labour Organization (ILO) — Generative AI and Jobs: A Refined Global Index of Occupational Exposure, Working Paper 140, 20 May 2025. The study estimates that one in four workers worldwide is employed in an occupation with some degree of exposure to generative AI and concludes that job transformation is, in most cases, more likely than complete replacement.

World Economic Forum — The Future of Jobs Report 2025, January 2025. Survey covering more than 1,000 employers representing over 14 million workers across 55 economies. Surveyed employers expect 39% of workers’ core skills to change or become outdated by 2030 and estimate that 59% of workers will require training.

OECD — OECD Skills Outlook 2025, 2025. The report examines changing skills requirements and highlights the growing importance of lifelong learning, reskilling and professional development, as well as persistent inequalities in access to adult education and training.

UNESCO — Guidance for Generative AI in Education and Research, 2023. International guidance on the integration of generative artificial intelligence into education and research through a human-centered approach.

UNESCO — AI Competency Framework for Students, 2024. Framework addressing the competencies learners need to understand, use and critically assess artificial intelligence in a responsible manner.

Websites

International Labour Organization: ilo.org World Economic Forum: weforum.org OECD: oecd.org UNESCO: unesco.org