Two AI Stocks Positioned for Exponential Growth in 2026: A Deep Tech Strategist's Analysis

The AI infrastructure build-out is now in its exponential phase. Spending is forecast to grow at a 31% annual rate through 2033, a multi-year paradigm shift that is already reshaping the global economy. This isn't a fleeting trend; it's the foundational layer for the next computing era. Yet the market is actively rotating away from the purest infrastructure plays, signaling a critical inflection point. Investors are no longer rewarding all big spenders equally. The divergence is clear: investors have rotated away from AI infrastructure companies where growth in operating earnings is under pressure and capex spending is debt-funded. This selectivity means the next beneficiaries must demonstrate a clear, profitable link between their capital deployment and revenue generation.

The bottleneck is shifting. The initial frenzy focused on GPUs, but the physical limits of data movement are now the constraint. As one analyst noted, "The bottlenecks moved from GPUs to the things that feed and connect them." This is the new frontier. Memory and optics are stepping into the spotlight, becoming the critical, high-value components that enable the AI stack to scale. The winners here are not the general contractors, but the specialized suppliers of these essential rails.

This is where CoreWeave and Atlassian are positioned to capture disproportionate value. CoreWeave operates at the performance edge of the AI cloud, providing the purpose-built infrastructure that feeds the most demanding workloads. Its platform is recognized as the benchmark for AI cloud performance. Atlassian, meanwhile, is a productivity beneficiary, offering the software tools that enable the human teams building and managing AI applications. Both companies are aligned with the next phase of adoption, where the focus is on efficiency, integration, and the specialized components that make the exponential growth possible.

CoreWeave: Capturing the AI Compute Power Bottleneck

CoreWeave is building the fundamental rails for the AI paradigm. As a neocloud, or GPU cloud, purpose-built for AI workloads, it operates at the performance edge of the stack. Its platform is recognized as the benchmark for AI cloud performance, having been ranked as the most capable provider of cloud AI services, scoring above tech giants Amazon, Microsoft, and Alphabet. This isn't just a marketing claim; it's a technical moat built on data centers engineered for the extreme power density, memory bandwidth, and cooling required by AI training and inference.

The company is positioned exactly where the bottleneck has moved. As the AI build-out accelerates, the constraint is no longer just raw GPU availability but the entire system that feeds and connects them. CoreWeave's specialized infrastructure is the critical link in that chain, making it a direct beneficiary of the exponential adoption curve. Wall Street sees this potential, with analysts estimating CoreWeave's revenue will increase at 94% annually through 2027. That kind of growth rate suggests the fundamental story is just beginning, with expectations for massive beats as demand consistently outpaces supply.

Valuation reflects both the high growth and the market's caution. The stock trades at a multiple of 8.4 times sales, which looks cheap against that trajectory. Current price action shows a significant pullback, with shares down from their highs. Yet the upside potential remains substantial. The median analyst target is $120, implying 36% upside from recent levels. More bullish estimates, like a $180 per share target, imply 105% upside. The key risk is the substantial debt used to finance its rapid expansion. But as revenue scales, that leverage should become less consequential, turning a financial burden into a strategic asset as the AI compute demand curve steepens.

Atlassian: The Productivity Beneficiary on the AI Software Stack

Atlassian is making a clear pivot from its traditional enterprise software roots to become a core provider of AI productivity tools. The company is transitioning from a business model reliant on long-cycle enterprise sales to one focused on accelerating adoption through its new AI assistant, Rovo. This shift is already showing explosive results in its commercial pipeline. In its latest quarter, U.S. commercial revenue grew 121% year over year, a growth rate that signals the beginning of a powerful adoption curve.

This isn't just a product update; it's a strategic alignment with the next phase of AI integration. As the infrastructure layer builds out, the next bottleneck is human productivity. Atlassian's platform is uniquely positioned to capture value by enabling the teams that build and manage AI applications. Its self-service model and focus on developer communities allow it to scale AI tools directly to the users who need them, shortening the sales cycle and driving rapid revenue acceleration. The setup is similar to a peer like Palantir, which recently demonstrated the explosive potential of this model by closing 204 deals of at least $1 million last quarter. Atlassian is building its own high-velocity sales engine for AI software.

Wall Street expects this trajectory to continue. Analysts project adjusted earnings will grow at 22% annually through the fiscal year ending in June 2027. That steady, high-growth path is reflected in the valuation. The stock trades at a current price of $139, with a median analyst target of $230, implying 65% upside. More bullish estimates, like a $320 per share target, suggest the market sees even greater potential. The key risk is the same one facing all AI software plays: the need to consistently deliver on the promise of productivity gains to justify the premium. But for a company that is both a beneficiary of the AI paradigm and a builder of its essential tools, the path to exponential growth is now clearly mapped.

Catalysts, Risks, and the Path to Exponential Adoption

The path to exponential growth for CoreWeave and Atlassian hinges on a few critical catalysts and watchpoints. The primary driver is the continued steepening of the AI adoption S-curve, which depends on two key factors: the commercialization of new chip architectures and the scaling of AI platform software. These developments will directly fuel demand for both specialized compute infrastructure and the productivity tools that manage it.

Leading indicators to watch are the quarterly capex beats from hyperscalers and memory price action. The consensus estimate for 2026 capital spending by AI hyperscalers has now climbed to $527 billion, up sharply from the start of the third-quarter earnings season. Yet investors have become highly selective, rotating away from infrastructure plays where capex is debt-funded and operating earnings growth is under pressure. This divergence means that any quarter where major cloud operators report stronger-than-expected AI spending will be a major positive catalyst, validating the growth trajectory. Similarly, memory prices are a direct signal of the physical bottlenecks in the system. A sustained rise would confirm that the demand for the specialized components CoreWeave provides is outstripping supply, accelerating the adoption curve.

The biggest risk is a flattening of that curve. This would occur if AI spending growth decelerates or if capital allocation shifts away from infrastructure toward other areas. The recent stock price divergence among hyperscalers, where correlation has fallen to just 20%, shows that the market is already pricing in this dispersion. If the link between capex and revenue generation weakens, the entire infrastructure build-out could face a period of re-rating and consolidation.

For CoreWeave, the catalyst is clear: as chipmakers like Nvidia and AMD roll out next-generation architectures, the demand for purpose-built, high-performance cloud platforms will surge. For Atlassian, the catalyst is its own pivot to AI productivity tools. The explosive growth in its commercial pipeline, with U.S. commercial revenue up 121% year over year, mirrors the high-velocity sales model of peers like Palantir. The key will be scaling this model to capture the next wave of AI software adoption. The path is set, but the journey will be defined by these near-term signals.