It is becoming increasingly clear that the approach to monetization differs significantly between companies within the hyperscaler space, depending on four key pillars: monetization, control of the technology chain, visibility into demand, and quality of spending.
Although they are usually grouped under the same investment theme linked to artificial intelligence, the major players Microsoft, Alphabet (Google’s parent company), Amazon, and Meta are developing very different business models. Beyond aggregate capital expenditure (CAPEX) figures, companies are not allocating their resources or monetizing AI at the same pace, nor are they building the same competitive advantages.
What matters now is less about the absolute magnitude of spending than the quality of that spending: whether it translates into greater visibility on demand, greater control over the technology chain, and ultimately a clearer path to transforming infrastructure investments into revenue generation. In this context, it is worth reviewing the business models and investment strategies of the major hyperscalers.
Microsoft is integrating AI into enterprise software, positioning itself as a key player in enhancing corporate workflows through tools like Copilot and Azure. Its partnership with OpenAI provided an early advantage, while Azure Foundry and its multi-model approach help reduce reliance on a single vendor. However, the main risk lies in software disintermediation if enterprise workflows evolve from traditional tools toward autonomous agents powered by third-party models.
Google is well-positioned due to its high degree of vertical integration across chips, models, and distribution in both consumer and enterprise products. Its infrastructure advantage is increasingly becoming more visible as it monetizes parts of its stack beyond internal use. The main risk for Google does not lie in an abrupt disruption of the Search business but rather in a gradual shift in how information is accessed, with AI Overviews and AI Moderation reducing reliance on traditional “blue links.” Despite this risk, search revenue continues to grow.
Amazon’s strategy hinges on flexibility, scale, and cost efficiency. Through AWS, Amazon provides the infrastructure, models, and tools necessary for developing both AI and non-AI applications, while proprietary chips like Graviton and Trainium improve price-performance ratios. The main risk lies in e-commerce, where AI agents could reduce the relevance of Amazon’s retail interface, weakening its direct relationship with customers and putting pressure on the advertising business. This is more a structural than an immediate risk.
Meta focuses primarily on strengthening its own platforms to increase engagement and improve advertising efficiency rather than selling infrastructure directly to third parties. Its monetization route is less direct but strategically significant. The main risk lies in the high level of investment in infrastructure, particularly as capital intensity increases without a significant public cloud business to absorb some of these costs.
Overall, hyperscalers remain one of the most relevant ways to gain exposure to the artificial intelligence investment theme, given their visibility on demand and ability to generate sufficient cash flows. However, they should no longer be considered interchangeable exposures within the same sector. As business models diverge, AI is increasingly becoming a story of stock-picking, determined by each company’s monetization capacity and risk profile.
Equities performed strongly throughout April, supported by favorable macroeconomic data that particularly boosted the main US and European indices. The S&P 500 recorded its best month since November 2020, while the Euro Stoxx 50 also posted significant gains. However, the market remained closely focused on inflation trends and the geopolitical context. Rising oil prices and growing expectations of a prolonged international conflict triggered a fresh spike in sovereign bond yields, particularly in the US and Germany.
Credit markets continued to show resilience despite the environment of geopolitical uncertainty, while oil prices remained high due to tensions surrounding Iran and the Strait of Hormuz, which continue to fuel supply concerns. Against this backdrop, CAPEX spending by hyperscalers remains robust, and the returns on these investments continue to perform well.
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