Microsoft and TSMC: The Scalable AI Infrastructure Play

The foundational demand for the AI infrastructure build-out is no longer a forecast-it's a global adoption wave. In the second half of 2025, roughly one in six people worldwide were using generative AI tools, marking remarkable progress for a technology that only recently entered mainstream use. This isn't just a Western trend; it's a worldwide diffusion, with adoption rates in the Global North now at 24.7% of the working-age population versus 14.1% in the Global South. The data shows a clear leader: the United Arab Emirates, where 64% of working-age residents are using AI tools. This surge in real-world usage is the ultimate validation signal for the massive investments Microsoft and TSMC are making in cloud capacity and advanced chip manufacturing.

That adoption wave is now being met with a powerful generational confidence. According to the 2026 AI Investor Outlook Report, 67% of Gen Z respondents highlighted their confidence in AI-powered investments generating long-term returns, compared to just 50% of baby boomers. This split underscores a critical dynamic: the younger cohort, which has grown up with digital tools, sees AI not as a passing fad but as a multidecade wealth-generating opportunity. Their enthusiasm is translating into market momentum, creating a virtuous cycle where widespread user adoption validates the infrastructure build-out, which in turn fuels further innovation and investment.

For investors, this sets up a clear thesis for long-term market capture. The growth driver is secular and global, moving beyond early-adopter markets. Microsoft's contracted backlog of nearly $400 billion and its plan to double its data center footprint signal it is positioning to capture this demand wave. TSMC's dominance in the chip foundry market, coupled with its advanced 2nm production, ensures it is the indispensable enabler of the compute power required. The investment case, therefore, hinges on these companies' ability to scale their operations to meet a demand that is no longer hypothetical but is being measured in hundreds of millions of users worldwide.

Microsoft's AI Growth Engine: Scale and Backlog

Microsoft's strategy is a masterclass in committing capital to capture a generational shift. The company is no longer just selling software; it is building the physical and digital infrastructure for the next decade of computing. This is evident in three staggering metrics that demonstrate a fully committed, scalable build-out.

First, the contracted backlog is a multiyear revenue guarantee. As of its fiscal Q1, Microsoft's total commercial remaining performance obligations-a measure of contracted future revenue-rose to nearly $400 billion. That figure, up 50% year over year, provides exceptional visibility and funds the aggressive expansion ahead. It signals that enterprise customers are locking in capacity far in advance, validating the scale of the demand.

Second, user penetration shows the platform is becoming essential. The company's AI features now boast over 900 million monthly active users, with more than 150 million of those using the Copilot assistant. This massive installed base is the foundation for recurring revenue and the primary driver of the soaring demand that is outstripping supply.

The third and most telling metric is the unprecedented capital deployment. In its fiscal first quarter, Microsoft spent $34.9 billion on capital expenditures, an all-time high for a single quarter in tech history. Roughly half of that went to the short-lived GPUs and CPUs that power AI, while the rest secured long-term control of land, power, and data center infrastructure. This isn't a budget allocation; it's a declaration of intent to scale compute at planetary levels.

Together, these elements form a powerful growth engine. The backlog ensures the pipeline, the user base drives the demand, and the capital expenditure is the fuel to build the capacity. Microsoft plans to double its data center footprint within the next two years and increase AI capacity by over 80% in the current fiscal year. The CFO has acknowledged the company will remain "capacity-constrained through at least the end of the fiscal year." This constraint is a direct result of the explosive adoption, and Microsoft is pouring capital to resolve it. For a growth investor, this is the ideal setup: a massive, visible demand signal met with a capital commitment that ensures the company can capture the lion's share of the market.

TSMC's Foundry Dominance and Advanced Node Premium

TSMC's role in the AI infrastructure story is not just important-it is the single most critical bottleneck. The company is the world's sole supplier of the advanced chips that power the AI revolution, and its control over the production chain gives it immense allocation power and a direct path to stronger earnings growth.

The financial results underscore this dominance. In the fourth quarter, TSMC reported revenue of $33.05 billion, a 20.45% year-over-year increase that beat analyst forecasts. This isn't just growth; it's growth driven by a specific, high-margin demand. The company's foundry market share stood at an incredible 72% in Q3 2025, and its fabrication plants are reportedly running at full capacity. This leaves little room for competitors and ensures TSMC captures the lion's share of the massive capital spending flowing into AI chips.

The real constraint, however, is emerging beyond the chip itself. TSMC controls the advanced packaging capacity-specifically its CoWoS technology-that is becoming a key bottleneck for AI scaling. This packaging integrates processors with high-bandwidth memory, and without it, finished AI accelerators cannot deploy at scale. The evidence is stark: Google reportedly cut its 2026 production target for its Tensor Processing Units from 4 million to 3 million units because of limited access to TSMC's CoWoS capacity. Nvidia has secured priority allocations, locking in over half of its available capacity through 2027, which leaves competitors scrambling. This dynamic means TSMC doesn't just make the chips; it controls the final, essential step in getting them to market.

This control translates directly into pricing power. Reports indicate that TSMC is preparing to charge a 10-20% premium for its advanced 2nm nodes. This premium is a direct function of scarcity and the irreplaceable nature of its technology. As chip designers compete for limited capacity, TSMC can dictate terms. This pricing power, combined with the sheer scale of its operations and the relentless demand for AI compute, sets up a powerful earnings trajectory. For a growth investor, TSMC represents the indispensable, scalable enabler of the AI build-out. Its ability to command a premium on next-generation nodes and control the packaging bottleneck ensures its earnings will continue to grow at a rate that outpaces the broader semiconductor market.

Scalability, Risks, and Long-Term Investment Thesis

The investment case for Microsoft and TSMC is a high-stakes race to scale. Both companies have demonstrated an extraordinary commitment to building the physical and technological infrastructure for the AI era. Microsoft's plan is to double its data center footprint within two years and has just committed an additional $4 billion to build a second AI data center in Wisconsin. This follows its initial $3.3 billion pledge for the first facility. TSMC, meanwhile, leverages its foundry dominance and control over advanced packaging to ensure it is the indispensable enabler of the entire hardware ecosystem. The scalability of their models is clear from the contracted backlog and the massive capital expenditure already underway.

Yet the path to dominance is fraught with execution risks. The primary constraint is not chip design, but the physical supply chain. Advanced packaging capacity, particularly TSMC's CoWoS technology, is a critical bottleneck. Reports show that Google reportedly cut its 2026 production target for its Tensor Processing Units due to limited access to this capacity. This packaging crunch is mirrored in another key component: high-bandwidth memory (HBM). The supply of HBM is already sold out for 2026, and providers like Micron, Samsung, and SK Hynix are securing better prices from multiple big tech buyers. These bottlenecks in packaging and memory could constrain the entire AI hardware ecosystem, limiting how quickly new models can be deployed and potentially creating a new layer of allocation power.

The core investment thesis hinges on which companies can scale their capacity faster than demand. For Microsoft, it's about securing the land, power, and construction to bring its planned data centers online on schedule. For TSMC, it's about expanding its CoWoS and HBM production to meet the insatiable demand from Nvidia, AMD, Google, and others. The foundational demand signal from the global adoption wave is undeniable, and both companies are building the scalable engines to capture it. Their ability to navigate these supply chain bottlenecks and maintain their capital deployment will determine whether they secure a durable, decades-long dominant position in the AI value chain. The risk is real, but the potential reward for those who succeed is the ownership of the infrastructure itself.