A McKinsey & Company’s June study warns that wage convergence in Hungary has proceeded faster than productivity growth, while employment rates have risen to high levels—making the previous growth model based on expanding employment unsustainable. The report, Prompt Hungary – The impact of artificial intelligence on the competitiveness of the economy, argues that artificial intelligence (AI) can be the main lever for a productivity turnaround, provided firms treat it as a driver of operational redesign rather than merely a technology add-on.
Current situation: wages, employment and productivity
According to the study, real wages in Hungary have increased by more than 50 percent since 2008, and employment now exceeds 80 percent. However, unit labor costs have risen much faster than productivity over the past decade. That gap implies that further wage convergence faces growing constraints and that the extensive growth sources—primarily employment expansion—have largely been exhausted.
AI’s potential and its limits
McKinsey Global Institute estimates that tasks theoretically replaceable by AI in Hungary amount to roughly €15 billion, equivalent to about 6–7 percent of Hungarian GDP. That figure is comparable to the total of certain EU funds that are currently becoming available following government negotiations.
The report cautions that technology alone will not automatically deliver productivity gains. Realizing the potential requires mindset shifts and the reorganization of workflows across both private and public sectors. The study highlights obstacles that can limit AI’s impact—such as structural inequalities in the economy, a frequently changing regulatory environment, and fragmented development funding.
At the same time, there are advantages to build on: a relatively advanced digital infrastructure and mature e-government systems can provide a foundation for introducing AI-based solutions.
Conditions for success: skills, operating models and data foundations
McKinsey identifies three main conditions for successful AI adoption: improving workforce skills, transforming corporate operating models, and strengthening data and technology foundations. Only the combination of these three elements can turn AI from a marginal process or cost tool into a core driver of productivity growth.
Five strategic areas for Hungary
The study points to five priority areas where AI could generate tangible productivity improvements relatively quickly:
- bringing small and medium-sized enterprises (SMEs) up to speed,
- education and reskilling,
- building sectoral AI champions,
- public administration modernization,
- healthcare transformation.
McKinsey partners emphasized both opportunity and responsibility. Havas András said: “The Hungarian economy can gain a head start if it exploits the opportunities in AI as soon as possible. There is now a chance to acquire capabilities that previously—due to lack of capital or adequate backbone infrastructure—were accessible mainly to traditionally advantaged, large and developed economies. AI can be an escape route for Hungary and the region, but its prerequisites should be sought less in the technology itself and more in the thoughtfulness and sophistication of its application.”
Matécsa Márta added: “AI affects every segment of the economy and changes the nature of work, which is why we argue that a comprehensive model shift is needed. Because of its diverse use cases, ease of access and cost-effectiveness, AI can awaken dormant innovation potential within SMEs, which could be an important engine of future economic growth.”
Conclusion
The McKinsey study identifies AI as a clear breakout opportunity for raising productivity in Hungary, but stresses that AI alone will not resolve the country’s structural challenges. Effective use of the technology requires deliberate application, process redesign and skills development across both public and private sectors. The report concludes that improvements in economic performance will come from broad, coordinated measures rather than from technology investments alone.
