Two AI Infrastructure Stocks Positioned to Beat the Market in 2026: Riding the Exponential Compute S-Curve

We are witnessing the birth of a new technological paradigm, and its foundational layer is being built at an exponential pace. The AI race is not just another software upgrade; it is a fundamental shift in how we process information, demanding a completely new species of infrastructure. In sprawling industrial parks, supersized buildings packed with racks of computers are springing up to fuel the AI race. These are not ordinary data centers. They are supercomputers designed to train and run large language models at mind-bending scale, complete with their own specialized chips, cooling systems, and even energy supplies. This is the physical manifestation of the AI compute S-curve entering its steepest, most profitable phase.

At the heart of this new infrastructure is a single, dominant standard. Nvidia has driven the performance of these AI factories into a new era. The company is driving annual performance improvements of five times, throughput of 10 times, and driving token demand of 15 times. This isn't incremental progress; it's a multi-order-of-magnitude leap that sets the economic rules for the entire ecosystem. In the same way Intel and Microsoft defined the personal computer era, Nvidia is becoming the mainspring of this new computing paradigm. For any player in the AI stack, aligning with this standard is no longer optional-it's a survival imperative.

The sheer scale of investment confirms this is a paradigm shift, not a trend. Tech giants are pouring hundreds of billions of dollars into this infrastructure. Yet, the market's consensus view has consistently lagged reality. Analyst estimates have consistently underestimated capex spending related to AI. This persistent underestimation is a classic sign of exponential adoption. It shows the market is struggling to grasp the accelerating pace at which hyperscalers are deploying capital. The recent divergence in stock prices among AI hyperscalers further underscores this. Investors are rotating away from infrastructure plays where capex is debt-funded and earnings growth is pressured, and toward those where the link between spending and revenue is clear. The setup is now for a new phase of the trade, one focused on platform operators and productivity beneficiaries who can monetize this massive, underappreciated buildout.

Stock 1: Broadcom (AVGO) - The Custom Compute Partner

Broadcom is positioned to ride the AI compute S-curve not as a pure-play chipmaker, but as a critical partner for the hypercalers building the new infrastructure. While Nvidia sets the performance standard, Broadcom is the company many of these giants are turning to for custom solutions. The company is partnering directly with AI hyperscalers to design custom AI accelerators, or ASICs. These chips are built for specific workloads, allowing them to outperform general-purpose GPUs at a lower cost. This partnership model is the key to Broadcom's explosive growth trajectory.

The financial setup is clear. Broadcom expects 51% growth for fiscal year 2026, a figure driven almost entirely by this AI infrastructure buildout. This isn't speculative; it's a direct translation of the massive capex being deployed by hyperscalers into concrete revenue for a key supplier. The company is a major wild card because this custom design work is happening now, with launches expected over the next few years. This gives Broadcom a multi-year runway of high-margin design and manufacturing contracts, insulated from the commodity price swings of standard chips.

This growth path aligns perfectly with the market's current rotation. Investors are rotating away from AI infrastructure companies where growth in operating earnings is under pressure and capex spending is debt-funded. Broadcom, however, is a productivity beneficiary in the making. Its custom ASICs are designed to make the hypercalers' massive investments more efficient and cost-effective. This creates a clear, value-creating link between the capex being spent and the revenue Broadcom captures. In a market that is becoming more selective, this is the kind of story that commands a premium. For a company with a $1.7 trillion market cap, 51% growth is a powerful signal that it is not just participating in the AI paradigm shift, but is a foundational layer of its economic engine.

Stock 2: Nvidia (NVDA) - The Compute Standard

Nvidia is not just a leader in AI; it is the foundational compute layer for the entire paradigm. The company has further solidified its position as the hardware and software standard for the next generation of computing, much like Intel and Microsoft defined the PC era. This dominance is not theoretical. It is quantified by the staggering performance leaps Nvidia is driving: annual performance improvements of five times, throughput of 10 times, and driving token demand of 15 times. This isn't just faster chips; it's a fundamental reset of the economic rules for AI factories. For any player in the stack, aligning with this new standard is the only path to relevance.

This creates a powerful, self-reinforcing adoption curve. The ecosystem Nvidia has built is the mainspring of the current innovation cycle. Its software stack, developer tools, and performance leadership lock in customers and partners, making it exponentially harder for alternatives to gain traction. The historical parallel is instructive: during the PC era, companies that challenged Intel simply could not keep pace due to its relentless cadence and scale. Nvidia is executing a similar playbook on a grander scale, where its own performance gains compound the demand for its infrastructure. This is the essence of an S-curve in action-the network effects and switching costs become a moat that widens with every new generation of chips.

The market's verdict is clear. Nvidia's stock has increased over 1,350% in the past five years, a figure that captures the explosive growth of the AI infrastructure buildout. This isn't a short-term pop; it's the valuation of a company that has become the essential rail for a new technological paradigm. The company's $4.6 trillion market cap as of early January underscores its role as the central platform. For investors, Nvidia represents the purest play on the exponential adoption of AI compute. It is the standard that everyone else must follow, and its growth trajectory is a direct function of the global race to build the next generation of intelligent systems.

Catalysts, Risks, and the Next Phase

The AI infrastructure S-curve is now in its steep, accelerating phase. The key catalyst for the next leg of this journey is the launch of custom computing units by the AI hypercalers. Broadcom is already partnering with these giants to design custom AI accelerators, or ASICs. As these specialized chips begin to ship over the next few years, they will validate the entire custom design model. This is a major catalyst for Broadcom and other partners, translating the massive capex being deployed into concrete, high-margin revenue streams. It signals that the efficiency race has begun, and the companies building the specialized rails will capture significant value.

Yet the primary risk to this thesis is the industry's ability to scale efficiency alongside raw compute power. The current model, reliant on massive GPU deployments, faces physical and economic constraints. As new agentic capabilities emerge, the demand for specialized chips like ASICs will intensify. If the industry cannot keep pace with this demand through smarter, more efficient hardware, the entire buildout risks hitting a wall. The efficiency frontier is the new battleground, and the companies that fail to innovate here will see their investments become stranded.

This sets the stage for the next phases of the AI trade. As the market becomes more selective, the rotation away from pure infrastructure is expected to continue. Goldman Sachs Research expects the next phases of the AI trade to involve AI platform stocks and productivity beneficiaries. Investors are already rotating away from companies where capex is debt-funded and earnings growth is pressured. The clear link between spending and revenue is the new metric of value. This suggests a potential shift in focus from the builders of the infrastructure to the operators and users who can monetize it. The setup is for a trade that rewards not just capital deployment, but the ability to convert that capital into tangible productivity gains.