Is a stock market crash coming? The AI ​​revolution is devouring its own children – share prices plummet at SAP, Palantir, Oracle, Salesforce & Co.

Software markets in free fall: Extent and reach of the sell-off

We examine whether this is a short-term correction or the beginning of a long-term crisis

The sell-off of software stocks on Wall Street has evolved from a subdued profit-taking into a massive correction cycle affecting large portions of the SaaS and enterprise software segments. Indices such as the S&P North American Software Index are retrospectively recording their largest monthly loss since the financial crisis, while the SPDR Software & Services ETF suffered double-digit losses within just a few days. The breadth of the movement is striking: not only niche players, but also established giants like ServiceNow, Oracle, Palantir, Adobe, Salesforce, and Autodesk are trading significantly lower than their end-of-2025 levels. The acute sell-off began in the US but quickly spread to Asian and European markets, creating a global phenomenon that can no longer be attributed to individual company figures or quarterly reports.

Within just a few weeks, individual stocks lost 20 to 30 percent or more of their value, even though their key operating figures remained stable or even showed strong growth in many cases. This demonstrates that the drivers are not primarily weak fundamentals, but rather focused on valuation and expectations. The combination of high valuations, completed AI rallies in infrastructure stocks, and an increasingly skeptical view of the long-term pricing power of software providers is driving the market into a new phase of risk assessment. Nervousness is particularly high among companies whose business models are based on recurring subscriptions and long-term licensing agreements—precisely where disruption from artificial intelligence is most immediately anticipated.

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AI anxiety as a systemic shock: From euphoria to skepticism

The main reason for the massive sell-off is the growing fear that AI models could render established software business models obsolete or at least put them under significant pressure. The new generation of AI—such as the comprehensive systems from Anthropic, OpenAI, and other providers—can not only support tasks but also increasingly automate entire work processes in legal, analytical, and administrative areas. For many companies, this translates into less human labor, less manual data entry, and therefore potentially less need for expensive software licenses per user. This threat is disrupting the traditional per-seat or per-user billing model, which for many SaaS providers has long served as the basis for substantial price increases and margin optimization.

The market is currently processing a fundamental shift in narrative: Until recently, artificial intelligence was a growth driver, generating additional demand for software licenses and cloud services. Now, AI is increasingly seen as a "substitution risk" that could particularly affect companies that have benefited from the wave of digitalization. The combination of such systemic fear and extremely high valuations is leading to rapid portfolio reallocations. Investors who previously focused disproportionately on AI-related winners and growth stars are reducing their positions and, in some cases, shifting their investments into less growth-oriented, but also less risky, segments. The result is a kind of "reverse flow": While infrastructure stocks such as chips and data centers continue to benefit, traditional software companies are becoming the focus of massive profit-taking.

ServiceNow, Oracle, Palantir & Co.: Who exactly is being crushed?

The sell-off is widespread, but clearly concentrated in certain company profiles. ServiceNow, a key provider of workflow, IT service, and enterprise automation solutions, has suffered significant double-digit share price declines since the beginning of the year, despite quarterly results demonstrating operational strength and rising revenues. Investors are not reacting to poor business performance, but rather to the question of how much AI assistants and automated workflows might influence future licensing agreements and pricing. A similar pattern is evident at Oracle: The stock has lost around a quarter of its value since the beginning of the year, even though demand for cloud and database services remains robust. The concern here is less about the demand for storage and database infrastructure per se, but rather about the company's ability to finance the high capital expenditures for AI data centers and manage its accumulated debt.

For years, Palantir profited from its role as an AI specialist for government, defense, and large corporations. However, since the beginning of the year, its stock has fallen significantly, demonstrating that the AI ​​hype no longer automatically propels every "AI ticket" forward. Skepticism is focused on the sustainability of margins, the scalability of revenues, and competition from other major platforms that integrate similar analytical capabilities. Adobe, Snowflake, Datadog, and numerous other software stocks share this pattern: strong operational performance, but a market drastically reducing valuations because the viability of individual business models is suddenly being questioned. The weakness is therefore less selective than it is widespread across industries and primarily affects companies whose value creation relies heavily on human interaction, administration, and manual processes—precisely the areas that AI systems can automate most rapidly.

Structural stress factors: valuations, AI investments and capital structure

Besides fears of AI disruption, several structural factors are impacting the software sector. Firstly, despite recent share price declines, the valuations of many companies remain high, measured by multiples such as revenue or EBITDA. The announcement of billions in AI investments by major cloud providers has further fueled expectations for revenue and profit growth, even though the actual increase in earnings is not yet tangible. Investors react sensitively as soon as growth stalls or the timeframes for the impact of AI investments lengthen. The fear that AI investments will initially increase costs while the revenue impact is delayed exacerbates this nervousness.

A second stress factor is the capital structure of individual software companies. Oracle, for example, has invested heavily in new data centers and AI infrastructure in recent years, accumulating considerable debt in the process. Discussions about financing risks and the withdrawal of large investors have heightened market awareness regarding the long-term sustainability of its balance sheet. Other providers are also facing significant capital commitments and high lease obligations, further impacting valuations. For companies with high equity costs and limited access to capital markets, any indication of financing bottlenecks can immediately trigger a valuation shock. This risk is particularly pronounced in a period of rising interest rates and stricter regulations.

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AI as both destroyer and builder: A new market structure is emerging

More than just a price drop? The fundamental reassessment of the entire software industry

Interestingly, the acceleration of AI not only threatens software providers but also massively supports certain other segments. Chipmakers, cloud infrastructure, and data centers are benefiting from the demand for AI-optimized servers and computing power. Companies like Super Micro Computer and specialized AI hardware providers are reporting significantly improved revenue forecasts and increasing order backlogs. The market is thus showing a clear dividing line: Value creation is shifting from the traditional software and application level to the infrastructure and platform level on which AI models run. At the same time, data, platform, and operations providers that can position themselves as the "operating OS" for AI applications are gaining strategic importance.

The dynamics are somewhat similar to previous technological disruptions: the real transformation isn't taking place in the end product, but in the underlying infrastructure. Those who manage to control the interface between AI models and existing business processes can benefit more in the long run than traditional software providers who rely on automating individual workflows. The current crisis in software stocks is therefore less an expression of a general decline in technology demand and more a sign that the market structure is realigning. The winners will not necessarily be the companies that have historically profited most from digitalization, but rather those that fully embrace the AI ​​revolution in their architecture and business model.

Overreaction or a new level of evaluation?

Many market observers describe the current phase as a potential overreaction – with a significant risk that the valuation adjustment will continue. The concern that AI systems will permanently curtail the growth trajectories and pricing power of software companies is real, but difficult to quantify. The valuations of many stocks have already fallen so sharply that slow but stable growth rates and moderate margins are already priced into current share prices. This creates an intriguing tension: some of the selling could be considered technically excessive, while at the same time a fundamental revaluation process is underway that cannot be reversed by a single quarterly report or erroneous AI hype.

For long-term investors, this means that selection becomes more crucial than mere industry affiliation. Companies that consistently integrate AI functionalities into their existing products, have scalable business models, and possess a solid capital structure are likely to recover from the correction cycle more quickly. The current weakness in software stocks can thus be both an opportunity for more defensive entry points and a warning that AI disruption is not merely theoretical, but has concrete, measurable valuation and marginal impacts on existing business models. The AI ​​revolution is therefore not only devouring its own offspring, but also reshaping the structure of the entire software landscape – with profound consequences for capital market value, competitive landscapes, and long-term value creation within the industry.

SAP in the AI ​​vortex: Valuation pressure and market sentiment

SAP is not only affected by this AI-driven sell-off of software stocks, but has become a prime example for the industry in Europe. SAP shares are among the biggest losers in the DAX in 2026, having plummeted by more than 20 percent since the beginning of the year – a decline unmatched by any other leading German index stock. The technical picture clearly shows that the shares have been under continuous pressure since the price slump at the beginning of January, reaching 17-month lows. At the same time, the price decline is part of a broader software correction phase, which is being felt both in Europe and on Wall Street. The company's market capitalization has fallen by ten-figure billions since its all-time high, underscoring the depth of the valuation adjustment.

Investor nervousness towards SAP is closely linked to fears that generative AI will replace traditional enterprise software, particularly in the cloud and SaaS sectors, or significantly diminish its value creation. SAP has benefited for years from the migration of many customers to the cloud and from recurring subscription revenues, which have historically been stable and predictable. However, the new generation of AI agents and platforms—such as specialized legal or analytical tools—could automate many standard processes for which companies previously purchased separate modules and licenses. This challenges the classic equation of "more employees = more licenses = more revenue" for some SAP products. The combination of this structural risk and a previous overvaluation is leading to a massive revaluation of SAP shares, even though the company's operating figures remain largely robust.

Despite stable or slightly growing revenue and solid profit development, the market is reacting sensitively to any hint of weakening cloud momentum. The latest annual forecast for cloud growth is at the lower end of market expectations, which investors are interpreting as a possible sign that the period of rapid cloud growth is slowing – precisely in an environment where fears of AI disruption are further depressing valuations. Many analysts continue to rate SAP as a quality stock with a solid balance sheet and strong cash flow, but see a clearly increased risk to the valuation in the short to medium term. The current valuation seems less like a judgment on the company's long-term viability and more like a hedge against uncertain AI effects and potentially weaker growth.

AI as a threat – but also as an opportunity for SAP

At the same time, SAP is increasingly positioning AI as a central theme of its own strategy. The company has embedded AI functions in numerous cloud applications and emphasizes that many new contracts are based on AI licenses. The vision of benefiting from AI-powered assistants and automations, rather than being displaced by them, is clearly articulated at the executive level. SAP is focusing on its role as an "AI enabler" in everyday business, accelerating standard processes, reducing errors, and lowering the effort required for routine tasks. In this scenario, AI is not seen as a mere cost center, but as a lever for productivity gains and thus potentially higher-value services.

Nevertheless, the question remains whether this narrative will convince the markets. Share prices react less to good technical integration than to the uncertainty surrounding the extent to which AI agents can undercut or completely circumvent existing licensing models. The fact that SAP has been simultaneously undergoing a €10 billion share buyback program and AI investments in recent months demonstrates the company's attempt to reassure investors while modernizing its technology base. The impact of this combination—high investments in AI infrastructure and new software development coupled with a cautious cloud outlook—makes SAP's stock valuation a particularly sensitive case within the industry. In the short term, the stock therefore remains a prime example of how AI concerns are impacting global software markets and sparing even established champions like SAP.

SAP as an early indicator for the software industry

SAP plays a key role in this AI sell-off: The stock is not only a flagship German company, but also a leading indicator of sentiment towards enterprise software in a global context. SAP's share price losses are structurally linked to those of ServiceNow, Oracle, Salesforce, Adobe, and others – they result from a similar combination of fear of AI disruption, high pre-valuation, and skepticism regarding the pricing power of traditional SaaS models. At the same time, SAP remains a company with high capitalization, stable cash flow, and deep customer loyalty, which makes the valuation adjustment painful, but not necessarily existential. While the AI ​​wave is also eroding SAP shares, it simultaneously makes the company a crucial test case for whether traditional ERP and business software giants survive as platforms and integrators in the new AI architecture, or whether they are left behind as "legacy" providers.

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