Cramer’s Verdict: Shrinking P/E Multiples Crush Software Giants Amid AI Fears

Stella Evans
Stella Evans

Jim Cramer blames collapsing P/E multiples for software stocks' rout amid AI disruption fears, spotlighting ServiceNow's 49% drop despite strong earnings. Microsoft and SAP followed suit on cloud slowdowns, signaling a sector bear market as investors demand proof of AI resilience.

Cramer’s Verdict: Shrinking P/E Multiples Crush Software Giants Amid AI Fears

Enterprise software stocks are in freefall, hammered by investor fears that artificial intelligence will upend their lucrative business models. On his CNBC show “Mad Money,” Jim Cramer pinpointed a single metric driving the carnage: the relentless compression of price-to-earnings multiples. “The market has turned against software stocks and this metric explains their downfall,” Cramer declared, as shares of high-quality names like ServiceNow plunged despite solid results.

Cramer described the P/E multiple as the “secret sauce” to understanding stock pricing, measuring how much investors will pay for each dollar of future profits. When growth confidence erodes, multiples shrink—a dynamic playing out brutally across the sector. ServiceNow, the poster child for this trend, dropped 9.9% Thursday after better-than-expected earnings and a massive buyback, with its forward P/E collapsing from the upper 60s in January 2025 to the 40s by April, and now under 28. Over the past year, ServiceNow shares have tumbled 49%, while the iShares Expanded Tech-Software Sector ETF fell 11%—lagging the S&P 500’s 15% gain by a wide margin, according to CNBC .

“Can the market be wrong? Of course, it’s wrong all the time,” Cramer said. But fighting the “freight train” of shrinking multiples is futile for now. He predicts these “great companies” could become buyable once multiples bottom out.

AI Disruption Sparks Valuation Reckoning

The root cause? Persistent worries that AI will disrupt traditional software workflows, from code generation to automation, eroding subscription revenue. ServiceNow CEO Bill McDermott appeared on “Mad Money” touting AI adaptation, yet the market voted him “off the island,” as Cramer put it. “The stock market has said, ‘Ain’t got nothin for you, Bill,’” he quipped. Earnings remain fine, but “what people will pay for those earnings” has cratered.

This sentiment rippled through the sector. Microsoft shares cratered nearly 10% Thursday after fiscal 2026 Q2 results topped estimates but revealed Azure cloud growth deceleration and surging AI capital expenditures. “This is largely Microsoft and software companies coming down because of Microsoft,” Cramer noted in a separate segment, per CNBC . Microsoft’s backlog reliance on OpenAI—45% of $625 billion—raised red flags, with operating margins forecast to dip to 45.1% amid infrastructure spends, as detailed by Forbes .

SAP’s shares plunged 15-16%—its worst day since 2020—after 2026 cloud revenue guidance of 23-25% growth and decelerating backlog missed expectations, dragging peers like Salesforce down 6.3%, Adobe 2.5%, and Datadog 5%, according to Reuters .

Sector-Wide Selloff Signals Bear Territory

The iShares Expanded Tech-Software Sector ETF (IGV) shed 5.4% in its largest one-day drop since April, with the S&P 500 Software and Services Index hitting a nine-month low after an 8.7% plunge. U.S. software stocks have posted double-digit annual declines as AI fears challenge SaaS models, per Reuters . On X, Cramer posted: “It’s the collapse of software and the ascent of hardware and it is staggering. Just staggering.”

Other names echoed the pain: Salesforce down 16% in recent sessions, Adobe and Workday struggling, as Cramer lamented uncertainty around AI rivals like Anthropic. Earlier, he advised steering clear of Datadog, saying enterprise software feels like “freefall,” via Yahoo Finance . X users highlighted the “Great SaaS Meltdown,” with Nasdaq 100 up 20% while the Morgan Stanley SaaS Index fell 20%, citing AI’s threat to per-seat pricing.

Jim Cramer on X reinforced the divide: software collapsing as hardware surges on AI infrastructure demand. Posts from analysts like @ThuanGlobal noted firms delaying long-term contracts amid AI automation, pushing the sector into bear market territory.

CapEx Surge and Cloud Slowdown Amplify Pressures

Microsoft’s woes stemmed from reversing prior guidance: after promising lower fiscal 2026 CapEx than 2025, it hiked spends, projecting Azure growth at 37-38% for Q3 but facing supply constraints, not demand weakness, as explained in Insider Monkey . Meta bucked the trend, rising 10% on AI-driven ad revenue acceleration, but Cramer warned against quarterly overreactions, citing Alphabet’s rebound on Gemini progress, per another CNBC piece.

Broader trends show investors rotating to semiconductors and memory plays like Micron, which tripled in 2025 on AI data center demand. Cramer cautioned against chasing those post-rally, favoring pullbacks, via CNBC . Software’s high-growth, low-profit model is “dead,” with profitability now paramount, as 24/7 Wall St. analyzed.

“I accept the market’s judgment at least for now, because I can’t fight it. It’s too powerful,” Cramer conceded on ServiceNow. Yet he remains bullish long-term: “Soon, when we see how low the multiple can go — and it will bottom — these may be worth buying.”

Investor Roadmap Through the Turmoil

For industry insiders, the P/E compression signals a valuation reset: software must prove AI integration boosts durable growth, not just offsets disruption. X chatter from @Bull1shPilot warns of the “seat crisis”—fewer users needed with AI efficiency. SAP’s backlog deceleration underscores execution risks, while Microsoft’s OpenAI dependency highlights partner vulnerabilities.

Cramer urges patience, avoiding fights with momentum. His Charitable Trust holds software exposure like CRM and MSFT, betting on rebounds. As hardware scarcity persists, software’s fate hinges on adapting to an AI-native world—where multiples reflect real profitability, not hype.

About the Author

Stella Evans
Stella Evans

Stella Evans is a journalist who focuses on AI deployment. They work through trend monitoring with careful context and caveats to make complex topics approachable. They believe good analysis should be specific, testable, and useful to practitioners. They examine how customer expectations evolve and how organizations adapt to meet them. Their reporting blends qualitative insight with data, highlighting what actually changes decision‑making. Readers appreciate their ability to connect strategic goals with everyday workflows. They write about both the promise and the cost of transformation, including risks that are easy to overlook. They also highlight cultural factors that determine whether change sticks. Their coverage includes guidance for teams under resource or time constraints. Their perspective is shaped by interviews across engineering, operations, and leadership roles. They often cover how organizations respond to change, from process redesign to technology adoption. They maintain a balanced tone, separating speculation from evidence. They are interested in the economics of scale and operational resilience. They prefer evidence over hype and explain trade‑offs plainly.

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