The downturn in software stocks isn't tied to current earnings. Instead, investors are repricing the entire sector, removing the premium they once paid for its perceived safety and stable, long-term contracts, which are now threatened by AI disruption.

The massive capital expenditure required for AI development is depleting tech giants' cash reserves. This reduces their ability to fund stock buybacks, which have historically acted as a major source of equity demand and a key volatility suppressant for the broader market.

Companies like Oracle and Broadcom face market corrections as investors confront the difficult realities of the AI buildout. Lower-than-expected margins, data center delays, and high capital expenditures are injecting a dose of reality into the previously overhyped infrastructure trade.

A primary risk for major AI infrastructure investments is not just competition, but rapidly falling inference costs. As models become efficient enough to run on cheaper hardware, the economic justification for massive, multi-billion dollar investments in complex, high-end GPU clusters could be undermined, stranding capital.

Initially viewed as a growth driver, Generative AI is now seen by investors as a major disruption risk. This sentiment shift is driven by the visible, massive investments in AI infrastructure without corresponding revenue growth appearing in established enterprise sectors, causing a focus on potential downside instead of upside.

Investors are selling off hyperscalers like Amazon for their massive $200B AI CapEx, fearing pinched profits. Simultaneously, software stocks are being punished for not investing enough in AI. This contradictory reaction highlights extreme market uncertainty about the right AI investment strategy.

The startup landscape now operates under two different sets of rules. Non-AI companies face intense scrutiny on traditional business fundamentals like profitability. In contrast, AI companies exist in a parallel reality of 'irrational exuberance,' where compelling narratives justify sky-high valuations.

The recent software stock wipeout wasn't driven by bubble fears, but by a growing conviction that AI can disintermediate traditional SaaS products. A single Anthropic legal plugin triggered a massive sell-off, showing tangible AI applications are now seen as direct threats to established companies, not just hype.

Software has long commanded premium valuations due to near-zero marginal distribution costs. AI breaks this model. The significant, variable cost of inference means expenses scale with usage, fundamentally altering software's economic profile and forcing valuations down toward those of traditional industries.