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As degrees multiply across advanced economies, their signaling power weakens. What once certified scarce expertise now risks becoming an inflationary currency. When credentials outpace competence, education shifts from productivity engine to sorting mechanism — straining meritocracy and reshaping the labor market.
Telefónica is a century old. Once, it embodied Spanish modernity in its most tangible form: cables, exchanges, uniforms, physical presence. Today, it is something else — or is attempting to become something else entirely. Less visible. More abstract. More algorithmic. The central question is no longer how Telefónica grows, but what it is becoming.
For more than a decade, artificial intelligence has been presented as a promise: smarter decisions, safer systems, better services. In recent months, however, AI has increasingly appeared in a different role — as a rationale for large-scale job cuts. Few announcements illustrate this tension more clearly than the recent restructuring at ABN AMRO.
AI is often discussed as a technology story, a policy headache or a race between continents. But if you step back, the most useful way to understand its trajectory is surprisingly traditional: the macro–meso–micro framework that economists have used for decades. It turns out to be an elegant map for a technology that is reshaping value creation from the planetary level down to individual workflows.
Europe does not lack talent. It lacks the gravitational pull to keep it. Across the continent, universities, labs and startups produce some of the world’s strongest AI researchers. Yet the same people often migrate to the U.S. or the UK, pulled by higher salaries, deeper compute access and faster-moving ecosystems. Europe cultivates brilliance, but struggles to convert it into long-term advantage.
If the past few years felt fast, 2025 is something else entirely. Suddenly everyone is talking about Kosmos, “AI scientists”, autonomous agents and systems that seem to learn, reason and create at unbelievable speed. But for most people, the AI world feels like a maze: many names, many models and very little clarity.
In an era defined by rapid technological change, geopolitical competition and accelerating innovation cycles, one truth cuts through all complexity: nations rise or fall on the strength of their talent. The next generation of thinkers, builders and innovators will determine whether economies can adapt — or be left behind.
Imagine walking into work tomorrow and finding a new colleague at your desk — gripping a coffee, humming softly, but with no face, no voice, only glowing code. That colleague? An algorithm. While that may sound futuristic, many workers already feel that AI is part of their team. What does it mean when machines don’t just assist, but collaborate? And how does trust, empathy and human experience shape this new way of working?
