Artificial intelligence deployment could generate €15 billion ($17.42 billion) in productivity improvements across Hungary's economy by 2030, according to a fresh analysis from McKinsey & Company released this week. The finding underscores how advanced technologies might help Hungary reduce its productivity deficit relative to Western European neighbours, though the consultancy cautioned that sluggish adoption could deepen Hungary's competitive disadvantage in an increasingly AI-driven global economy.
The productivity opportunity identified in the McKinsey report reflects growing recognition across Central Europe that artificial intelligence represents both a transformative opportunity and a potential threat. For a mid-sized economy like Hungary, which has historically competed on manufacturing cost and skilled labour advantages, the shift towards AI-enabled operations carries profound implications. Falling behind in AI adoption would not simply mean slower growth; it could mean ceding market share to competitors in wealthier nations where the technology diffuses more rapidly.
Executives from Hungary's largest companies offered nuanced perspectives on how AI would reshape their sectors and the broader economy. Andras Becsei, deputy chief executive of OTP Bank, Hungary's dominant banking institution, cautioned that the financial impact of AI would be more complex than simply trimming payroll costs. While artificial intelligence might reduce certain human resources expenses, he noted that companies would simultaneously face rising operational costs and capital expenditure requirements to build and maintain AI systems. The net effect would represent a fundamental transformation of cost structures rather than a straightforward reduction, meaning organisations must plan for substantial restructuring rather than simple efficiency gains.
The telecommunications sector has already begun deploying AI at meaningful scale. Peter Nagy, deputy CEO of Magyar Telekom, Hungary's largest telecom operator, revealed that artificial intelligence now handles approximately one-fifth of all customer service calls, with that proportion expected to climb significantly. More strikingly, Magyar Telekom has compressed the timeframe for launching new services from ninety days to roughly thirty days through AI-assisted development processes. The company has also reallocated approximately half of its network monitoring staff to more sophisticated technical roles, allowing human expertise to focus on complex problem-solving rather than routine surveillance tasks. This redeployment pattern suggests that AI's primary value lies not necessarily in eliminating jobs wholesale but in elevating the nature of work performed by remaining staff.
The pharmaceutical industry, a significant economic sector within Hungary, confronts particular uncertainties about AI's genuine transformative potential. Gabor Orban, chief executive of Richter Pharmaceuticals, one of Central Europe's largest drugmakers, urged caution about separating genuine productivity advances from temporary hype cycles. Orban observed that the pharmaceuticals sector has weathered several previous technology-driven disruptions—including genomics and comprehensive digital transformation—that ultimately delivered far less dramatic results than their initial proponents anticipated. The pharmaceutical development process remains fundamentally constrained by regulatory requirements and scientific uncertainty, limiting how much artificial intelligence alone can accelerate innovation without changes to the broader regulatory environment.
Perhaps most provocatively, Gergely Bacso, head of Allianz Hungary, reframed the AI question as fundamentally about competitive positioning rather than simple cost reduction. Bacso argued that the labour cost savings available to large American technology companies deploying AI could exceed those available to Hungarian enterprises by a factor of several multiples. This asymmetry creates a structural competitive disadvantage: advanced economies with higher baseline labour costs find AI investments more economically justifiable, while lower-cost economies like Hungary struggle to achieve comparable returns. Without aggressive AI adoption, Hungary risks surrendering market share to foreign competitors who can more profitably leverage the technology to undercut prices or improve service quality.
This competitive dimension carries particular significance for Hungary within the broader European and global context. The country has traditionally attracted foreign direct investment partly through lower wage costs relative to Western Europe. If artificial intelligence makes labour cost advantages increasingly irrelevant—by enabling companies to substitute capital for labour at scale—Hungary must rapidly develop alternative competitive advantages. These might include AI research talent, specialised industrial applications, or regulatory frameworks that attract technology investment, but none materialises automatically without deliberate policy and business investment.
The McKinsey analysis arriving at €15 billion in potential productivity gains provides a quantified target, but the gap between identified opportunity and realised benefit remains substantial. Hungary's successful capture of these gains depends on multiple convergent factors: adequate capital investment in AI infrastructure, sufficient technical talent to implement and manage systems, organisational willingness to restructure roles and workflows, and policy frameworks that support rather than hinder adoption. The roundtable discussion with leading executives suggests awareness of these requirements is growing, yet translating awareness into coordinated action remains challenging across a dispersed economy.
For Malaysian and Southeast Asian readers, Hungary's situation offers instructive parallels and contrasts. Like Hungary, many Southeast Asian nations have relied on cost advantages and emerging manufacturing capabilities to attract investment and drive growth. The AI revolution threatens to erode these advantages while simultaneously offering opportunities for countries that can harness the technology effectively. The Hungarian experience suggests that capturing AI-driven productivity gains requires not just technology deployment but fundamental rethinking of organisational structures, workforce skills, and competitive strategy—a transformation more complex and demanding than simply purchasing software or hardware.
