Emerging Markets Post Strongest Earnings Growth in 20 Years on AI Infrastructure Spending
Morgan Stanley analysts are calling it: emerging-market companies are experiencing their strongest earnings growth in two decades, and the catalyst isn't traditional manufacturing or commodity exports—it's capital expenditure on artificial intelligence infrastructure.
The finding, published by Morgan Stanley on February 27, arrives as CFOs across developed markets wrestle with their own AI spending decisions. While much of the AI investment narrative has centered on U.S. tech giants and their hyperscale data center buildouts, the earnings impact is showing up most dramatically in the balance sheets of emerging-market firms that supply the physical infrastructure.
Here's the thing everyone's missing: when Microsoft or Google announces another $50 billion in capex, that money doesn't stay in Redmond or Mountain View. It flows to semiconductor fabrication plants in Taiwan, server manufacturers in Southeast Asia, and power infrastructure providers across emerging economies. The earnings growth Morgan Stanley is tracking represents the other side of the AI spending boom—the companies actually building the stuff.
The timing is notable. Emerging-market earnings growth has been relatively anemic for most of the past decade, with commodity price volatility and currency headwinds creating persistent drags. That this reversal coincides precisely with the AI infrastructure buildout suggests something structural rather than cyclical.
For finance leaders, the implication cuts both ways. On one hand, it validates the scale of AI-related capital deployment—you don't generate "strongest in two decades" earnings growth from vaporware. Real money is moving, real infrastructure is being built, and real profits are being recognized. On the other hand, it raises the question of sustainability. Infrastructure buildouts are lumpy by nature. They create earnings spikes during construction phases, then normalize once the capacity is operational.
The Morgan Stanley analysis (though the source article was truncated before providing specific figures or regional breakdowns) arrives as CFOs face increasing pressure to articulate their own AI investment theses to boards and investors. The narrative has shifted from "should we invest in AI?" to "how do we measure return on AI investment?" Seeing where the actual earnings are accruing—not just in the companies deploying AI, but in the supply chain enabling that deployment—provides at least one data point.
There's also a geographic arbitrage question embedded here. If emerging-market suppliers are capturing significant earnings from AI capex, it suggests the cost structure for AI infrastructure may be more favorable in those markets than conventional wisdom assumes. That could influence build-versus-buy decisions for companies planning their own AI infrastructure, or at least inform vendor negotiations.
The broader pattern: AI spending is no longer a theoretical exercise in PowerPoint decks. It's showing up in actual earnings, in actual markets, creating actual winners and losers. The question for CFOs isn't whether AI spending is real—Morgan Stanley's emerging-market earnings data confirms it is—but rather where in the value chain their own companies sit, and whether they're positioned to capture returns or just write checks.
What remains unclear from the Morgan Stanley analysis is how long this earnings surge sustains. Infrastructure buildouts eventually complete. The companies posting record earnings today may face tougher comps tomorrow. But for now, at least, the AI capex story has moved from promise to profit—just not necessarily where everyone was looking.
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