Nvidia steadies as software rout leaves AI capex intact

Why the $2T software wipeout didn’t derail the AI bull market

The recent $2 trillion software stock sell-off rattled sentiment but did not upend the AI bull market because the core growth engine, enterprise adoption built on expanding infrastructure, remains intact. Based on data from Business Insider, cloud providers lifted AI-related capital expenditure by roughly 69% across 2025, a scale of investment that tends to underpin multi-year compute demand rather than a single-quarter trade. That backdrop helps explain why the downturn appears more like a valuation reset than a collapse in AI-driven fundamentals.

Institutional analysts have separated short-term fear from medium-term cash-flow potential, noting that AI monetization in software typically trails infrastructure by several quarters. The distinction matters: training and inference need chips and data centers now, while enterprise applications layer in AI features as deployment, compliance, and workflow redesign mature. In that sequencing, hyperscaler capex can support the bull market’s foundation even as application-layer expectations are repriced.

What triggered the recent software stock sell-off

As reported by S&P Global Market Intelligence, the S&P North American Technology Software Index fell more than 20% year over year, with many SaaS names down 25% to 30% from peaks, after fresh catalysts stoked disruption fears. The report highlights concerns arising from new AI assistants and plug-in ecosystems, alongside surging hyperscaler capex, which together sparked debate about whether AI could displace parts of the incumbent software stack. Those headlines amplified uncertainty around pricing power, margins, and the pace of customer migrations.

Editorial analysis of earnings call commentary indicates that the market may be extrapolating early AI feature demos into sweeping replacement scenarios. As summarized by the Economic Times, JPMorgan’s Mark Murphy urged caution against assuming rapid substitution of mission-critical systems, citing the embedded nature of compliance, security, and vertical functionality. That assessment aligns with historical adoption curves in enterprise technology, where integration cycles, governance, and change management moderate the speed of disruption.

Executives at major chip and platform companies have also pushed back on the most extreme displacement narratives, emphasizing the early state of enterprise AI deployment. Rene Haas, CEO of Arm, called the panic “micro-hysteria,” a reminder that proof points from pilots and early AI copilots must still translate into durable, at-scale customer outcomes. In practice, that translation typically hinges on budget cycles, measurable productivity, and vendor integration roadmaps.

Immediate market impact and what investors should watch now

Market action has been blunt across technology, but not all parts of the AI stack face the same near-term fundamentals. As reported by MarketWatch, analyst Vivek Arya noted that strong and ongoing AI hardware needs make the sell-off in some chip names, Nvidia included, internally inconsistent with demand required for training and inference. That disconnect suggests the drawdown reflects cross-asset de-risking more than a collapse in underlying workload growth.

Forward-looking tracking often centers on operating performance rather than headlines. Investors commonly monitor net revenue retention, remaining performance obligations and billings, gross margin trajectories, and the mix and discipline of share-based compensation, alongside tangible AI monetization progress in seats, usage, or premium tiers. If hyperscaler capex were to slow materially, application vendors would likely lean harder on efficiency, attach, and upsell metrics to demonstrate resilience.

At the time of this writing, as contextual background from digital-asset markets, Render (RNDR) is quoted at $1.32 with very high 18.39% volatility, nine green days in the last 30, and an RSI(14) of 37.05, according to the provided metrics. While crypto tokens and listed software equities are distinct, such readings illustrate risk appetite variability across AI-adjacent assets without implying direction.

Sentiment versus fundamentals: earnings strength and valuation reset

Earnings breadth remains a counterweight to the recent drawdown. As reported by Fortune, roughly 75% of S&P 500 constituents had filed fourth-quarter results, with per-share profits 12% higher year over year, a sign that aggregate corporate profitability has not rolled over. While software valuation multiples compressed, that reset occurred against a backdrop of still-solid earnings power across the broader index.

Valuation resets can serve a constructive function in longer cycles by aligning price with achievable adoption timelines and capital efficiency. In AI software specifically, clearer unit economics, disciplined expense management, and evidence of workflow-level productivity gains may help re-anchor multiples. If those signals firm up while hyperscaler investment remains supportive, the AI bull market case can persist even after a severe software stock sell-off.