Oportunidades en la infraestructura de IA: Acciones que podrían duplicarse en 2026

The case for AI infrastructure stocks isn't about a fleeting trend. It's about a multi-year, high-growth secular buildout with a massive Total Addressable Market. The numbers point to ample headroom for value creation, with the global AI market projected to hit $4.8 trillion by 2033. This isn't just a future promise; it's a present-day race to build the physical and digital backbone. As JLL notes, AI hyperscalers and data center operators will race to build the computing capacity needed for the artificial intelligence boom. This capacity crunch creates a powerful tailwind for companies positioned to supply it.

Within this trend, three specific plays stand out for their potential to double in value this year. They represent different legs of the infrastructure chain, each with explosive growth trajectories. First is Nebius, a data center operator spun out of Yandex. It's selling out its capacity, with its annual run rate expected to surge from $551 million at the end of Q3 to $7 billion to $9 billion by the end of 2026. That's a potential tenfold expansion in a single year, a growth rate that could easily double the stock. Second is Applied Digital, which builds and operates data centers and is a key partner for CoreWeave. It reported an 84% year-over-year revenue jump in its fiscal Q1 2026, and with long-term leases in place, its revenue is set to climb as more computing capacity comes online. The third name is SoundHound AI, which blends generative AI with audio recognition. While a software play, its platform has the potential for monster adoption across industries, and widespread deployment could trigger a growth explosion.

These companies are capturing outsized returns because they are directly monetizing the AI infrastructure buildout. They are not just beneficiaries of the trend; they are essential suppliers in the race to meet unprecedented demand. For a growth investor, the thesis is clear: the secular TAM is vast, and these specific data center and AI software operators are positioned to capture a disproportionate share of that growth, making a doubling of returns a plausible outcome in 2026.

Growth Trajectories and Market Capture

The dominant players in AI infrastructure are not just riding the wave; they are engineering the wave. Their business models are built for scalability, and their financials show they are capturing a growing share of the massive infrastructure spend. For a growth investor, the trajectory of these giants is a key indicator of the trend's durability.

Nvidia's position is foundational. Its GPUs are the essential accelerators for AI training and inference, making it the direct beneficiary of every new model and application. The company's growth is explosive and self-reinforcing. In its third quarter of fiscal 2026, revenue hit $57 billion, up 62% year-over-year, driven by a record $51.2 billion in data center sales, which were up 66% YOY. This isn't just a spike; it's a sustained ramp-up that demonstrates the company's ability to scale its core product to meet surging demand. CEO Jensen Huang's comment that "cloud GPUs are sold out" underscores the capacity constraints and pricing power Nvidia holds. Its roadmap, with new architectures like Rubin, aims to lock in customers deeper into its ecosystem, ensuring it captures a disproportionate share of the AI compute dollar for years to come.

Amazon's strength lies in its dominant cloud platform, AWS, which provides the essential operating environment for AI workloads. Its growth is steady and diversified, benefiting from both enterprise lock-in and its own massive capital investments. In the third quarter, Amazon reported net sales growth of 13% on a year-on-year basis to $180.2 billion, with AWS sales growing at a much faster pace of 20%, to $33 billion. This 20% growth rate in a massive base shows AWS's scalability. Amazon is also making the strategic capital investments needed to fuel this growth, with capital investments of $92.3 billion for the first nine months of 2025 and projections for even higher spending in 2026. This spending isn't a cost; it's a bet on capturing more of the AI infrastructure market by expanding its capacity and services.

Microsoft's trajectory highlights the power of integrating AI directly into its cloud and software services. Its Azure cloud platform is a critical battleground, and its growth here is a leading indicator of AI adoption. In its first quarter of fiscal 2026, Azure and Cloud services revenue grew 40% year-over-year. That's a powerful signal that enterprise customers are not just using cloud capacity but are actively deploying AI services. This integration creates a sticky, recurring revenue stream that scales efficiently with each new AI model or feature Microsoft adds. The company's overall revenue growth of 18% to $77.7 billion in that quarter is supported by this high-margin, high-growth cloud engine.

Together, these three companies represent the core of the AI infrastructure stack. Nvidia provides the compute, Amazon provides the cloud platform, and Microsoft provides the AI services layer. Their scalable models and accelerating growth rates confirm that the infrastructure buildout is not a speculative bubble but a fundamental, multi-year shift in capital expenditure. For investors, the question is less about whether the trend will continue and more about which of these dominant, scalable players is best positioned to capture the next phase of growth.

Valuation and Financial Health Context

The financial health of these growth leaders is robust, but their valuations demand exceptional execution. The broader US market trades at a 4% discount to fair value, a figure that is skewed by the lofty prices of mega-cap tech. Excluding Nvidia from the calculation would raise the market's price/fair value metric to 0.98, highlighting how much its valuation drags the average higher. For AI stocks, the bar is even steeper. As Morningstar notes, artificial intelligence stocks require even stronger growth to support lofty valuations. This sets a high-wire act for companies like Nvidia, which trades at a trailing P/E of around 48 and a price-to-cash flow multiple of 61, implying sky-high expectations are already baked in.

Amazon's financial picture shows the classic trade-off of scaling a massive operation. Its Q3 operating income of $17.4 billion was roughly flat year-over-year, but that includes a $4.3 billion charge for one-time items. This masks underlying margin pressure as the company invests heavily in its AI infrastructure buildout, with capital spending projected to rise further in 2026. The growth is undeniable, but sustaining it while protecting profitability is the key challenge.

Microsoft, by contrast, demonstrates the cash flow power of a mature, high-margin growth engine. Its Q1 2026 revenue grew 18% to $77.7 billion, powered by a 40% surge in Azure and Cloud services. This strength allowed it to return $10.7 billion to shareholders via dividends and buybacks in the period. The company's financial health is solid, providing the flexibility to fund its AI ambitions while rewarding investors.

The bottom line is one of high expectations versus proven execution. Nvidia's valuation is a bet on sustained hyper-growth, while Amazon's path involves navigating expansion costs. Microsoft's model shows how to generate ample cash to fuel growth and return capital. For a growth investor, the financial health of these giants is sound, but their stock prices are pricing in near-perfect outcomes. The coming year will test whether their growth trajectories can justify those lofty valuations.

Catalysts, Risks, and What to Watch

The path to doubling returns in AI infrastructure stocks hinges on a few clear catalysts, significant risks, and specific metrics that will signal whether the thesis is accelerating or stalling.

The primary growth catalyst is the relentless pace of AI adoption and the resulting enterprise spending on data center capacity. As JLL forecasts, AI hyperscalers and data center operators will race to build the computing capacity needed for the artificial intelligence boom. This isn't a one-time build-out; it's an ongoing cycle of demand that fuels capital expenditure. For stocks like Nvidia, Amazon, and Microsoft, this means sustained, high-growth revenue streams from their core infrastructure businesses. Any acceleration in enterprise AI projects or new model launches could act as a near-term catalyst, spiking demand for GPUs, cloud services, and networking gear.

The key risk to this thesis is volatility stemming from lofty valuations. As Morningstar notes, artificial intelligence stocks require even stronger growth to support lofty valuations. This sets a high bar. If quarterly results from the hyperscalers show any sign of demand softening or margin pressure, the market's patience for perfection could evaporate quickly. The recent pullback in Nvidia's stock from its October highs illustrates this vulnerability. While the long-term TAM is vast, the near-term path is likely to be bumpy, with prices swinging on any deviation from hyper-growth expectations.

For investors, the metrics to monitor are the quarterly results from these giants, which will provide real-time data on demand and execution. Watch for Nvidia's continued data center sales growth, which powered 66% year-over-year revenue growth in its third quarter. For Amazon, track the health of its AWS segment, which grew 20% to $33 billion in the third quarter. And for Microsoft, the momentum in Azure and Cloud services, which surged 40% year-over-year in its first quarter, is a leading indicator of enterprise AI spending. Sustained double-digit growth across these key metrics is the essential signal that the infrastructure buildout is on track to double returns.

The bottom line is one of high conviction meeting high risk. The catalysts are powerful and structural, but the valuations leave little room for error. The coming quarters will test whether the explosive growth trajectories can justify the prices, making quarterly results the most important watch item for doubling outcomes.