The World Economic Forum (WEF) was not created as a technology summit. When Klaus Schwab founded it in 1971, Davos was conceived as a space for dialogue among political leaders, business executives and policymakers seeking coordination in an increasingly interdependent global economy. For decades, finance ministers, central bankers and heads of state set the tone. Technology firms were present, but rarely dominant.

That balance began to shift in the mid-2010s. When Schwab himself introduced the concept of artificial intelligence (AI) as the "Fourth Industrial Revolution. Since then, AI moved from being a sectoral issue to a structural one. While AI was initially focused on innovation, as its importance and impact became clear, it increasingly became a matter of power. Since then, AI has entered political discourse as a strategic asset shaping competitiveness, sovereignty, geopolitical rivalry and the overall balance of power.

AI dominated WEF

The most recent WEF meeting, which took place a couple of days ago, demonstrated how complete that transformation has become. Two issues defined the gathering: U.S. President Donald Trump’s speech and AI. On the surface, Trump’s speech, geopolitical positioning and discussions surrounding Greenland commanded headlines. Yet even these conversations are inseparable from AI policy, considering that his interest in Greenland is not only about territory but about access to critical minerals, strategic positioning and technological autonomy in an era where AI infrastructure defines national strength. In this sense, even discussions framed as traditional geopolitics in Davos were embedded in the politics of AI, once again showing its importance in international affairs.

As for AI, it has gradually moved from the margins of technical panels into plenary discussions about geopolitics, economic growth and global governance. In that sense, this year was not different. AI still dominated most of the panels and discussions. However, this year technology representation reached its clearest peak yet: alongside nearly 100 officially designated Technology Pioneers, large delegations from AI firms, semiconductor companies and digital platforms pushed the number of tech-affiliated participants well beyond 200, making the technology sector one of the largest organized blocs among the roughly 3,000 attendees.

The physical landscape of Davos reinforced this reality. The main street, historically overtaken by banks, consultancies and global brands, was overwhelmingly dominated by technology houses this year. AI firms, chipmakers and platform companies occupied prime locations, hosting events and branding spaces that projected confidence and inevitability. The visual message was unmistakable: technological power has become central to global governance.

If we were to consider WEF as a barometer of elite priorities, then it can be argued that AI is no longer a peripheral theme but embedded in the architecture of international relations. However, to gain a better understanding, it is important to examine how AI was addressed at Davos and what the main discussions around it were.

AI and labor market

The first major axis of AI discussion in Davos concerned employment. The discussion centered on the likelihood that AI will transform labor markets on a scale reminiscent of past industrial revolutions, only this time unfolding at a much faster pace. International institutions presented data suggesting that a significant share of jobs in advanced economies will be altered by AI, some enhanced, others transformed and some eliminated. Particular attention was given to the vulnerability of entry-level roles. If automation disproportionately affects early-career tasks, younger workers may struggle to access stable professional pathways. Therefore, the implications for social mobility and middle-class stability are profound.

On the other hand, in more optimistic tones, prominent technology leaders emphasized that AI can augment human productivity, particularly in health care, education and research. In emerging markets, AI-enabled systems were presented as a means of compensating for shortages of skilled professionals. The promise is efficiency and expanded access.

Furthermore, the employment debate also included political stability. Rapid labor displacement has historically fueled social unrest and populism. In a period already marked by polarization and geopolitical fragmentation, large-scale workforce disruption could exacerbate existing tensions. AI, therefore, is not merely an economic variable. It is, without a doubt, a political risk multiplier.

Expectations vs. reality

In this framework, the discussions appeared to coalesce into two distinct camps. On one side were the major technology firms with a confident and forward-looking message: AI is beginning to pay off. Enterprise adoption is accelerating, revenue streams from AI services are expanding, and generative tools are moving from experimentation into core business processes. Financial institutions are integrating AI into coding and analytics. Startups speak of rapid scaling across industries. For this group, the transition from infrastructure-building to measurable productivity gains is already underway. Some went further, suggesting that artificial general intelligence (AGI) may arrive sooner than many expect, reinforcing the sense that exponential breakthroughs are just over the horizon.

But there was another current running through, quieter but increasingly persistent. A number of investors, policymakers and analysts expressed caution about the scale of current expectations. While AI tools are spreading, the magnitude of enterprise-wide productivity gains remains uneven. Many companies are still in pilot phases. Systemic transformation has not yet matched the scale of capital expenditure. The distance between headline innovation and structural economic impact remains significant.

It is within this tension that a familiar debate has resurfaced: the possibility of an AI bubble. The concern is not that AI lacks transformative potential, but that financial and political expectations may be outpacing practical delivery. If anticipated returns fail to materialize at the projected speed, capital markets could correct sharply. The AI bubble, in this view, would burst because our expectations outrun reality.

This debate becomes even more consequential in light of geopolitical uncertainty. In a previous op-ed, I raised the possibility that Trump’s economic and trade policies could contribute to an AI slowdown. Protectionist measures, tightened export controls and strategic industrial prioritization may complicate global supply chains and capital flows that underpin AI expansion. If geopolitical fragmentation deepens, the growth trajectory of AI may prove less linear than current projections assume.

Against this backdrop, sustaining momentum is not just a market imperative for major technology firms, but it is a geopolitical strategy. High valuations, massive infrastructure commitments and long-term capital expenditures require continuous confidence from investors, regulators and governments alike. By projecting an image of rapid breakthroughs, near-term transformative gains and accelerating capability, Big Tech is reassuring markets, but most importantly, it is shaping global policy expectations.

The narrative of imminent AGI and sweeping productivity transformation does more than support stock prices. From a geopolitical perspective, it places pressure on states. Governments are compelled to accelerate national AI strategies, expand subsidies, secure semiconductor supply chains and align regulatory frameworks with technological competition. In this sense, corporate optimism becomes a form of structural influence. The faster AI appears to advance, the less room states feel they have to hesitate.

This dynamic unfolds within an already fragmented geopolitical landscape. The U.S. and China remain locked in technological rivalry, with AI at its core. At the same time, friction between the U.S. and Europe has intensified. Europe’s dependence on American AI platforms, cloud infrastructure and semiconductor ecosystems has become a strategic vulnerability. At the same time, calls for European digital sovereignty are growing louder. Furthermore, the Greenland question adds more to the friction between the U.S. and Europe

Organizing logic of Davos

WEF revealed more than enthusiasm for AI. It exposed a shift in leverage. Specifically, technology firms are no longer merely adapting to state policy, but they are increasingly shaping it. By projecting rapid breakthroughs and accelerating timelines, they pressure governments to align budgets, regulations and diplomacy with corporate technological trajectories. In doing so, AI becomes not just an innovation agenda, but a strategic imperative embedded in national policy.

This shift carries consequences for the international order. As the U.S. and China deepen technological rivalry and Europe wrestles with dependence and digital sovereignty, complicated further by disputes such as Greenland, cooperation grows more fragile and regulatory regimes diverge. Therefore, once again, we see how AI is structuring the global competition. So, the question is no longer whether AI will shape international relations as it already does. However, the real question is how this fusion of corporate ambition and geopolitical rivalry will redefine the balance of power in the years ahead.