How AI Will Separate Winners From Losers, According to Alejandro Betancourt López
Alejandro Betancourt López does not frame artificial intelligence as a technology story. He frames it as a structural reorganization of where value accrues in every industry simultaneously — and he makes a clear distinction between those who will benefit and those who will not. His basis for that distinction is specific rather than general, and it comes with a personal track record: an AI position placed roughly five years before the generative wave that had returned approximately 20 times its original value by early 2025.
What makes his framework worth examining is that it does not rely on predicting which specific companies or technologies will win. It relies on reading the structural shift and positioning capital in the right part of the value chain before the destination becomes obvious to everyone else.
Betancourt’s Core AI Thesis
He described AI’s function in direct terms: “What is AI? It’s a machine that thinks faster and finds solutions faster. So AI just makes everything more efficient. It’s not only in energy — in anything.” That definition is deliberately functional rather than technical. AI is not a sector. It is a capability layer that alters competitive dynamics across every existing industry, from energy production to consumer goods distribution to financial services.
The implication for investors is that AI exposure is not a matter of buying the right technology company. It is a matter of identifying which positions in every value chain will be strengthened by AI-driven efficiency gains — and which will be compressed. Betancourt’s early AI investment reflected the former thesis. His current focus on AI, robotics, and technology manufacturing reflects an extension of the same logic into the hardware layer.
The Winners and What They Have in Common
Betancourt’s account of who benefits from the digital revolution is structural rather than sector-specific. Winners will be those positioned in the right part of the value chain at the right moment. He made the observation explicitly: “There are going to be a lot of winners, a lot of losers, and it’s just interesting times to live through.”
McKinsey research cited by workforce analytics firm Gloat estimates that more than 70% of skills sought by employers today apply in both automatable and non-automatable roles. The human contribution to productive work does not disappear with AI adoption — it relocates. Workers and investors who identify where it is relocating and move there early are the winners Betancourt is describing. The pattern is identical to the VTC license thesis: read where the value is going, not where it has been.
What the Losers Face
Betancourt acknowledged the disruption without softening it: “A lot of new jobs are going to be created, but unfortunately a lot of traditional employment is going to be lost or replaced by this revolution.” The World Economic Forum’s Future of Jobs Report 2025 quantifies the tension: 92 million jobs displaced, 170 million created, net gain of 78 million — but only for workers who successfully transition.
The 40% of employers in the WEF survey who expect to reduce headcount in automatable roles are not describing a distant scenario. They are describing decisions being made now. Betancourt’s Industrial Revolution parallel is instructive: the factory economy that emerged from that period ultimately produced broadly shared prosperity, but workers caught mid-transition did not share in it on the way up. He argues the digital equivalent will move faster and require faster adaptation.
