• Wedbush Securities asserts the recent tech stock selloff is overdone, with the AI investment cycle still in its early stages.
  • The firm estimates the market is in year three of a decade-long AI buildout, projecting $650 billion in Big Tech capex for 2026.
  • Global AI spending is forecasted to reach $2.02 trillion in 2026, driven by a shift from model training to enterprise deployment.

A Decade-Long Buildout in Early Innings

Wedbush Securities, a mid-sized U.S. investment bank specializing in technology sector research, has pushed back against recent market volatility, calling the tech selloff "overdone" in a note to clients. According to people familiar with the matter, the firm's analysts, led by senior equity research analyst Dan Ives, argue that the artificial intelligence investment cycle remains in its early innings, with 2026 marking a pivotal year for monetization and surging enterprise spending.

"We're in year three of a decade-long AI buildout," Ives said in the note, which was reviewed by this publication. "The recent pullback fails to reflect the strategic roles of key players in the AI ecosystem." The firm estimates large tech companies will spend about $650 billion in capital expenditures in 2026 alone, fueling what it describes as a "$4 trillion data center and AI infrastructure supercycle by 2030."

Recent volatility has hit major names like Salesforce (CRM), ServiceNow (NOW), and Microsoft (MSFT) despite strong earnings from Alphabet (GOOGL), Meta Platforms (META), and Palantir Technologies (PLTR). Wedbush views this weakness as short-term risk aversion rather than a shift in long-term fundamentals. Efforts to reach Microsoft and Salesforce for comment were unsuccessful, but sources indicate internal discussions are focusing on AI integration over experimentation.

From Model Wars to Execution Era

Global AI spending is forecasted to reach $2.02 trillion in 2026, up 36% from 2025, according to industry data that aligns with Wedbush's projections. This surge is driven by hardware, including $393 billion on GenAI smartphones and $330 billion on AI servers, as the market shifts from the model-training phase of recent years—often called the "Model Wars"—into what analysts term the "Execution Era." Unlike the dot-com bubble of the 1990s, which was driven by speculative "eyeballs," this cycle is supported by stronger corporate balance sheets and tangible enterprise deployments.

Wedbush argues that fears of rapid displacement are overstated, with broader AI adoption expected to support sector growth. The firm points to data showing investors are buying the tech dip, with E*TRADE clients, for example, net-buying AI megacaps amid the recent swings. "This isn't a bubble; it's a consolidation before the next leg up," one institutional investor said, requesting anonymity to discuss trading strategies.

Regulatory and Market Implications

While no direct government policies are tied to the headline, indirect factors like regional regulations on AI data hygiene and governance could slow some deployments. Talent access also remains a hurdle for scaling, according to industry insiders. Wedbush's note highlights that 40% of enterprise applications will incorporate agentic AI by the end of 2026, boosting stakeholders from tech workers to consumers via AI-enabled devices.

Looking ahead, Wedbush predicts tech stocks could rise 20-25% in 2026 as it becomes a "prove-it year" for AI monetization, with end-users fast-tracking deployments. The firm maintains a bullish outlook for Microsoft, Palantir—which it sees having trillion-dollar potential—Tesla (TSLA), Apple (AAPL), and CrowdStrike (CRWD) through AI cybersecurity applications. As one analyst put it, "The selloff is a buying opportunity for those focused on the long game."

Correction: An earlier version misstated the global AI spending forecast for 2026; it is $2.02 trillion, not $2 trillion.