What AI Bubble? Why JPMorgan Says AI Stocks Are Becoming Popular Again

For nearly two years, critics warned that artificial intelligence equities were headed toward a classic speculative collapse. Rising valuations, massive capital expenditures by hyperscalers, and investor concentration in a handful of mega-cap technology firms triggered comparisons to the dot-com era. Yet in early 2026, one of Wall Street’s most influential voices—JPMorgan Chase—has pushed back decisively against the bubble thesis and instead signaled that AI stocks are regaining momentum.

According to JPMorgan analysts, investor concerns about overspending on AI infrastructure temporarily slowed enthusiasm late in 2025. But those fears are now fading as computing shortages persist and enterprise demand continues accelerating. The bank recently raised its year-end S&P 500 target partly because of renewed excitement surrounding artificial intelligence companies and stronger earnings expectations tied to AI adoption.

Rather than a speculative surge detached from fundamentals, the AI trade increasingly resembles the early build-out phase of a new industrial platform. Massive capital investment is being matched by rising enterprise usage, infrastructure bottlenecks, and the emergence of high-margin software services layered on top of foundation models. The result is a market narrative shift from “AI bubble” to “AI monetization cycle.”

Why JPMorgan Believes AI Stocks Still Have Room to Run

The key argument behind JPMorgan’s bullish view is simple but powerful: demand for AI computing capacity continues to exceed supply. That imbalance alone supports sustained capital investment across the ecosystem. Investor anxiety earlier this year centered on whether companies like hyperscale cloud providers were spending too aggressively on infrastructure. But analysts now point to the opposite problem—there is still not enough computing power to support advanced model training and enterprise deployment. Anthropic’s new Mythos platform and expanding enterprise adoption helped reignite investor confidence by demonstrating strong revenue momentum and reinforcing the need for additional infrastructure capacity. Even more striking is the scale of expected investment. The four largest hyperscalers are projected to spend approximately $645 billion on AI-related capital expenditures in 2026, representing a 56 percent increase year over year. Such spending levels are incompatible with a collapsing investment theme. Instead, they signal the opposite: a structural transformation underway across cloud computing, enterprise software, and digital infrastructure.

The AI Infrastructure Shortage Is the Market’s Hidden Catalyst

Much of the early AI rally was driven by semiconductor leaders. But the next phase of growth is shifting toward infrastructure platforms that enable large-scale model training and inference.

Companies operating AI cloud environments, GPU clusters, and specialized data centers are becoming essential links in the technology value chain. As a result, investors are increasingly focused on infrastructure providers rather than only model developers. This shift is critical because infrastructure firms generate recurring revenue through long-term contracts with enterprise customers and foundation model companies. That creates a more durable earnings base than speculative technology bets alone. It also explains why names like CoreWeave and Nebius are emerging as bellwethers for the next stage of the AI cycle.

CoreWeave Is Becoming a Central Player in the AI Compute Economy

CoreWeave represents one of the most important infrastructure stories in artificial intelligence today. Originally known for GPU-focused cloud services, the company has evolved into a specialized provider of high-performance compute environments tailored for foundation model training.

A major catalyst for investor enthusiasm came when CoreWeave secured a multiyear agreement to provide computing capacity to Anthropic for its Claude family of models. The deal immediately boosted the company’s stock price and reinforced its role as a strategic infrastructure partner for next-generation AI platforms. CoreWeave also signed a multibillion-dollar cloud contract with OpenAI prior to its IPO, demonstrating that foundation model developers increasingly rely on specialized compute partners rather than traditional hyperscale platforms alone. These partnerships illustrate a deeper structural shift in the market: infrastructure providers are becoming indispensable intermediaries between semiconductor innovation and enterprise AI deployment.

Nebius Is Emerging as a Surprise Leader in the AI Cloud Race

While CoreWeave receives most of the headlines in the United States, Nebius Group is quietly becoming one of the fastest-rising infrastructure players globally. Headquartered in Amsterdam, Nebius focuses on building full-stack AI cloud environments designed specifically for training and deploying advanced models. Its strategy emphasizes vertically integrated infrastructure rather than general-purpose cloud services. Investor enthusiasm has followed performance. Nebius shares have significantly outpaced CoreWeave in 2026, rising roughly 70 percent year-to-date compared with about 40 percent for its rival. This divergence highlights how the AI infrastructure race is expanding beyond Silicon Valley into a global competition for compute leadership. As a result, Nebius is increasingly viewed as a bellwether for international demand in AI infrastructure markets.

Software Stocks Are Quietly Staging a Comeback

During the early stages of the AI rally, software companies faced skepticism from investors who feared foundation models would commoditize traditional enterprise applications. But that narrative is beginning to reverse. According to JPMorgan, enterprise software stocks are already rebounding after a temporary slowdown driven by concerns about competition from model providers. The reason is straightforward: AI models require software ecosystems to create value. Enterprises still need workflow automation, analytics platforms, integration layers, and security frameworks to deploy AI at scale. Instead of replacing software companies, artificial intelligence is expanding their addressable markets. This dynamic mirrors earlier computing cycles in which infrastructure innovation ultimately boosted—not reduced—software demand.

OpenAI and Anthropic IPO Expectations Could Reshape the Market

Few events could energize the AI equity narrative more than public listings from foundation model developers themselves. Both OpenAI and Anthropic are widely expected to pursue initial public offerings, potentially as soon as late 2026. If these IPOs materialize, they could become some of the largest technology listings in history. Anthropic alone has reportedly reached valuations approaching $800 billion following major investment from Amazon. Public market access to foundation model companies would fundamentally change how investors allocate capital across the AI ecosystem. Instead of investing indirectly through cloud providers or semiconductor firms, investors could gain direct exposure to the companies building the core intelligence layer of the new digital economy.

That shift would likely trigger a new wave of institutional participation.

Enterprise Adoption Is the Real Story Behind the AI Rally

The most persuasive argument against the AI bubble narrative is enterprise adoption itself.

Unlike earlier speculative technology cycles, artificial intelligence platforms are already delivering measurable productivity gains across industries ranging from healthcare and finance to manufacturing and logistics. JPMorgan analysts emphasize that today’s AI investment cycle is supported by real revenue growth rather than purely speculative expectations. This distinction matters enormously.

During the dot-com era, many companies lacked viable business models. Today’s AI leaders generate billions in revenue, maintain strong balance sheets, and operate inside established enterprise ecosystems. That combination makes the current rally structurally different from past speculative bubbles.

Hyperscaler Spending Is Fueling the Next Expansion Phase

Another reason JPMorgan remains bullish on AI equities is the continued commitment of hyperscale cloud providers to infrastructure investment. Companies such as Microsoft, Alphabet, Meta Platforms, and Amazon are dramatically increasing capital expenditures to support model training, inference workloads, and enterprise deployments. These investments create powerful multiplier effects across the technology ecosystem. Semiconductor manufacturers benefit from increased GPU demand. Infrastructure providers gain long-term compute contracts. Software companies gain new integration opportunities. Enterprises gain productivity tools. Together, these forces reinforce the long-term investment thesis behind AI equities.

Infrastructure Deals Are Becoming the Market’s Leading Indicator

One of the most overlooked signals in the AI sector is the growing number of long-term compute agreements between infrastructure providers and foundation model developers. For example, CoreWeave’s partnerships with Anthropic and OpenAI demonstrate that capacity demand is not theoretical—it is contractually locked in. Similarly, multiyear infrastructure agreements are becoming common across the ecosystem as companies compete to secure scarce GPU resources.

These deals serve as leading indicators of future revenue growth because they effectively guarantee compute utilization before facilities even come online. For investors, that visibility reduces uncertainty and strengthens valuation confidence.

Why the AI Cycle Looks More Like an Industrial Revolution Than a Bubble

The phrase “AI bubble” implies unsustainable speculation detached from economic reality.

But the evidence increasingly points in the opposite direction. Artificial intelligence is driving one of the largest infrastructure investment cycles since the rise of the internet itself. Data centers are expanding. power grids are being upgraded. enterprise workflows are being redesigned. and software platforms are being rebuilt around machine intelligence. Even JPMorgan’s broader strategic outlook describes AI as a transformation comparable to the emergence of computing itself. That perspective reframes the entire investment conversation. Instead of asking whether AI stocks are overvalued, investors are beginning to ask whether the market is still underestimating the scale of the transformation ahead.

Volatility Is Normal During Platform Transitions

None of this means AI equities will rise in a straight line. Technology platform transitions always involve volatility. In fact, analysts note that AI stocks experienced multiple pullbacks during 2025 and early 2026 as investors reassessed spending levels and adoption timelines. But volatility is not the same as a bubble. It is the natural behavior of markets adjusting to rapid technological change. The key question is whether adoption continues accelerating. So far, the answer appears to be yes.

Investors Are Beginning to Reprice the AI Opportunity

When JPMorgan raised its 2026 market outlook, it was responding not just to macroeconomic stabilization but also to renewed investor enthusiasm around artificial intelligence. Confidence is returning because the AI narrative is shifting from experimentation to commercialization. Compute shortages remain unresolved. enterprise adoption continues expanding. infrastructure providers are signing multiyear contracts. and potential IPOs from OpenAI and Anthropic could introduce entirely new investment categories to public markets. Taken together, these signals suggest that the AI trade is evolving rather than ending.

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