Palantir on the Steep Part of the AI Infrastructure S-Curve: Strategic Data Moat Widens as Competition Falters

The next phase of AI growth is no longer about the apps or the chatbots. It's about the physical and digital rails that make them run. We are now in the industrial build-out stage, where the primary value is captured by the companies constructing the fundamental infrastructure. This is the steep part of the adoption curve, where exponential growth in spending meets a productivity paradigm shift.

The scale of this build-out is staggering. Morgan Stanley estimates that nearly $2.9 trillion in global data center construction cost alone will be deployed through 2028. More than 80% of that spending is still ahead, creating a multi-year tailwind for the entire supply chain. This isn't speculative tech spending; it's capital-intensive industrial expansion that feeds directly into GDP, power grids, and services. The market is beginning to price in this reality, as seen in recent sector rotations and valuation resets.

The key to capturing value lies in the productivity gains that follow adoption. Companies that move beyond pilot projects to implement AI see tangible results. According to Morgan Stanley, these adopters are achieving cash flow margin expansion at roughly 2x the global average. This isn't a minor efficiency tweak; it's a fundamental paradigm shift in how businesses generate profit. The market is paying for this evidence of monetization, not just mentions of AI.

This sets up the core investment thesis: value accrues exponentially in the infrastructure layer. While end-users see linear adoption and margin improvements, the builders of compute, energy, and data centers experience exponential revenue growth driven by this massive, multi-year capital expenditure cycle. The winners will be the firms embedded in this build-out, from chipmakers and power providers to construction and specialized software. The geopolitical competition for secure domestic infrastructure only elevates the strategic premium on these companies. In this new industrial era, the infrastructure is the asset.

The 5 Overlooked Picks: Exponential Growth Metrics

The market is pricing in the AI infrastructure build-out, but the steepest part of the adoption curve is still ahead. These five overlooked companies are positioned to capture exponential growth as the industrial expansion accelerates. Their metrics show not just strong performance, but the kind of scaling that defines a paradigm shift.

First, consider Broadcom. The semiconductor giant is not just riding the AI wave; it is building the custom silicon that powers it. Management's target is a fivefold increase in AI chip revenue, from $20 billion in 2025 to $100 billion in 2027. That's a quintupling over two years, a trajectory that transforms a massive existing business into a new exponential engine. The stock's recent pullback, driven by broad market selling, may have created a buying opportunity ahead of this ramp.

Next is CoreWeave, the pure-play AI cloud infrastructure provider. Its growth is visible in its order backlog. The company reported a 271% year-over-year increase in revenue backlog in Q3 2025. This isn't just revenue; it's a forward-looking indicator of demand that will convert into cash flow over the coming quarters. For a company in the early stages of its own build-out, this kind of backlog expansion signals a steep adoption curve.

Stepping back from the pure-play AI names, Jabil exemplifies the industrial scaling happening across the supply chain. The electronics manufacturing services leader has seen its data center business boom as demand for AI servers surges. The stock's 58% gain over the past year reflects this hidden infrastructure play, where the company is a critical, often overlooked, link in the chain.

For a smaller, high-margin player, look at SoundHound AI. The company is doubling down on the productivity gains of AI voice technology. Its revenue doubled last year and grew 59% in the fourth quarter. More importantly, it is achieving this growth with expanding profitability, as its adjusted gross margin expanded 800 basis points last quarter to 60.5%. This combination of exponential top-line growth and margin expansion is a hallmark of a company moving up its own S-curve.

Finally, there is Palantir. The company's success with its AIP platform has created a wide moat. Its $329 billion market cap and the lack of direct competition in its core government and enterprise data integration space underscore its strategic position. The platform's adoption is widening its competitive advantage, turning it into a less risky, more predictable play on the long-term data infrastructure paradigm.

These companies represent different points on the infrastructure stack, but they share a common thread: they are all in the steep part of the adoption curve. Their metrics show exponential growth trajectories that are just beginning to accelerate.

Valuation, Catalysts, and Deep Tech Risks

The investment case for these infrastructure plays rests on a simple equation: exponential growth potential versus near-term volatility and structural risk. The market is currently in a phase of recalibration, where the headline risk of massive capital spending is pressuring even the largest AI beneficiaries. This has created a choppier environment where the narrative of pure AI growth is being tested against real cash outlays. As one strategist noted, you've clearly seen that breakdown in terms of the monolithic AI trade, with megacap shares and entire sectors like software and wealth management seeing significant sell-offs. The key catalyst here is that this volatility may be creating buying opportunities in the underlying infrastructure builders, whose growth is more tangible and less tied to fleeting software narratives.

The primary driver for all these companies remains the relentless deployment of capital. The catalyst is the sheer scale of the build-out still ahead. Morgan Stanley estimates that nearly $3 trillion of AI-related infrastructure investment will flow through the global economy by 2028, with more than 80% of that spending still to come. This isn't a one-time boom; it's a multi-year industrial expansion that will feed revenue for years. For companies like Broadcom, CoreWeave, and Jabil, this is the fundamental tailwind. Their exponential growth metrics are directly tied to this capital expenditure cycle, making the projected spending a powerful, forward-looking catalyst.

The most significant risks, however, are geopolitical and technological. The U.S.-China rivalry over chips and compute is a central theme, elevating the strategic premium on secure domestic infrastructure. This competition is a double-edged sword. It creates a massive, government-backed market for compliant domestic suppliers, but it also introduces friction and potential supply chain bottlenecks. The risk is that this rivalry could slow the adoption curve if it leads to fragmented standards or increased costs for global firms. As Morgan Stanley notes, U.S.-China competition across chips, compute, energy, and data will elevate the strategic premium on secure domestic infrastructure. This is a key risk for any company reliant on global supply chains or open markets.

A parallel risk is technological adoption lag. The promised productivity gains from AI infrastructure are the engine for monetization, but they must materialize. If the cash flow margin expansion seen by early adopters does not spread broadly and quickly enough, it could pressure valuations across the board. The market is now paying for evidence of monetization, not just mentions. As the software sector's recent drawdown shows, the concern that they're just spending far too much money is a real one. If the productivity payoff lags, the justification for massive capex could weaken, creating a feedback loop of lower expectations and higher volatility.

The bottom line is that these overlooked infrastructure stocks are positioned for the long, steep part of the adoption curve. Their value is tied to a multi-trillion-dollar build-out that is still in its early innings. Yet they are not immune to the market's current AI headline risk or the structural challenges of geopolitical friction and adoption timing. The investment thesis requires patience to ride through the volatility, betting that the exponential growth in compute and data center spending will ultimately validate the infrastructure build-out.