After the 2008 financial crisis, Western Europe experienced labour-market disruptions—lasting unemployment, fewer entry-level positions and fiscal austerity—that are now affecting Hungarian graduates. COVID-19 amplified the shock, and the rapid spread of artificial intelligence (AI) is adding a structural and likely permanent pressure: many tasks traditionally filled by entry-level workers risk being automated.
What has happened so far
- The 2007–2008 crisis brought a sharp rise in unemployment and in many places created persistent joblessness. Governments responded with cuts and welfare retrenchment; in Mediterranean countries the 2010s saw sustained structural unemployment.
- High labour costs and strict regulation in Western Europe pushed companies to move production to cheaper new EU member states, which in turn created Central European service and shared-service centres (SSC).
- In Hungary, from about 2013, weaker forint, flexible labour rules and an available skilled workforce attracted investment; unemployment fell significantly by 2014–2015 and the trend continued until 2020.
- The COVID-19 pandemic in 2020 caused a global halt and the subsequent recovery did not remove all damage. From 2022 Hungarian unemployment figures began to rise again; companies imposed hiring freezes and entry-level and internship positions saw heavy oversubscription.
AI’s effects are not temporary
The article stresses that AI’s spread will structurally reduce entry-level jobs. This is more than simple chatbots: platforms and AI agents can perform real-time tasks similar to human employees. Because many AI systems are developed and run by other automated systems, the net job-creation effect—especially for Central European labour markets—may be limited.
Different pressures on white‑ and blue‑collar entrants
- White-collar entrants: office, customer-service and basic professional roles are vulnerable to AI replacement; diploma-holding graduates risk unemployment if they cannot secure appropriate entry positions.
- Blue-collar entrants: manufacturing and physical jobs face rapid automation as well, particularly in large plants. Some trades (plumbers, electricians, shelf-stockers) may have a temporary window, but weak vocational training and a shortage of practical placements reduce their prospects.
Consequences and risks
- An increase in solo self-employment among blue-collar entrants is likely, bringing unpredictable income, constant availability, and loss of pay during sickness.
- Oversubscription for poorly paid public-sector or quasi-public jobs can grow, as seen in Western Europe. A 25% youth unemployment rate in some cohorts is not inconceivable within a few years.
- The author projects that by 2040 two-thirds of new entrants and at least half of existing workers will be “hurt”: they will either fail to find work (new entrants) or see their jobs disappear or be downgraded (experienced workers). Jobs will become a luxury and competition for vacancies will intensify.
Social implications
Long spells of unemployment and what the author calls labour‑market “melting” (where entrants abandon their trained profession for lower-status work to survive) will increase poverty risks and social tensions. The article cites Mediterranean examples from the 2010s where some graduates shifted into agriculture or municipal manual work because those posts offered a stable paycheck.
Conclusion
The article offers a bleak outlook: structural weaknesses exposed after 2008, intensified by COVID-19 and now accelerated by AI, mean many of today’s graduates in Hungary may not reach their parents’ living standards and could be worse off. The number of stable, predictable jobs is expected to decline, irregular and precarious work to become more common, and inequality to rise. While the piece hints at the need for policy responses, retraining and financing options, it does not set out detailed remedies.
(The piece appeared in Portfolio’s “on the other hand” opinion column; the views expressed are the author’s.)
