The recent sell-off in enterprise software stocks, triggered by new products from Anthropic, reveals an excessive market panic regarding the threat of artificial intelligence. Barclays points out that investors are overlooking a crucial technical distinction: while AI tools are indeed encroaching on the application layer business of SaaS companies, they currently cannot disrupt the underlying "system of record" infrastructure—which constitutes the core moat for companies like Salesforce and SAP.

The launch of products like Claude Cowork by Anthropic last week acted as the final catalyst for the downturn in enterprise software stocks. Customer relationship management software stock Salesforce and financial management software stock Workday have both fallen over 40% in the past 12 months. This panic selling stems from a vague understanding among investors about the boundaries of AI capabilities. There is a widespread belief that new-generation AI tools from Anthropic and OpenAI will completely replace traditional SaaS software, rendering established companies worthless.

However, according to a Barclays report titled "Software Is Not Dead, Just Changing," released on February 10th, this simplistic, one-size-fits-all logic does not apply to most enterprise software companies.

**What AI Can and Cannot Do** The inherent strength of generative AI lies in pattern recognition and "first-draft generation," but its probabilistic nature also imposes fundamental limitations. AI excels at tasks requiring pattern extraction from vast datasets, such as natural language processing and code writing, but struggles in scenarios demanding absolute accuracy.

The Barclays report notes that traditional software operates on deterministic rules, where identical inputs always produce identical outputs. In contrast, AI software is inherently probabilistic, functioning through learned behavior rather than hard-coded logic, and cannot guarantee consistent output every time. This means AI operates at a higher level of abstraction and is not a direct replacement for traditional software.

This technical characteristic defines the applicable boundaries of AI. In contexts tolerant of errors, such as knowledge work and content generation, AI can replace or even surpass traditional SaaS applications. However, in areas requiring a single correct answer—like bill processing, compliance audits, and execution of business rules—AI is not yet capable.

Independent analyst Benedict Evans highlights that successful SaaS products arise from mapping unique organizational problems into workflows, which are then encoded into software. These years of accumulated, customized business rules form the infrastructure for businesses like banks, hospitals, and retailers, and are the foundation for companies like Epic Systems and Oracle.

**The Misjudged Half: The 'System of Record' Layer's Resilience** The Barclays report clearly identifies three types of enterprise software companies that have been mispriced in the sell-off and warrant investor re-evaluation.

The first category is system of record companies. For instance, Salesforce, as a customer relationship management system, holds the "single source of truth" for a company regarding customers and revenue—critical data like deal progress, discount approvals, sales commissions, and revenue forecasts, all requiring deterministic answers.

SAP's position is even more entrenched. As the system of record for enterprise finance, SAP CEO Christian Klein emphasized during the January earnings call that advanced generative AI models cannot handle the critical business data and workflows essential to a company's survival. Barclays considers SAP to have even stronger customer stickiness than Salesforce due to the irreplaceable nature of financial truth. Workday holds a similar position in human resources and payroll.

Far from being replaced, these systems are likely to see their importance grow. AI agents will create more data touchpoints, increasing the complexity that systems of record must handle. The Barclays report states, "This implies these systems become more important, not worthless, contrary to market views."

**Data Tools and AI Compute Sectors Also Misjudged** Beyond system of record companies, the Barclays report points to two other investment opportunities misunderstood by the market.

The second category consists of beneficiaries of AI agents. AI will generate increased demand for code and data. Tools like JFrog (FROG), which manage software artifact versions and security, and data vendors like Snowflake (SNOW) and MongoDB (MDB), could see increased usage due to AI expansion.

The third category is AI compute providers. Here lies a major market contradiction. If AI is powerful enough to disrupt the entire software industry, demand for computing power should surge dramatically. Yet, companies like Oracle and CoreWeave have been hit hard in the sell-off. "There must be a flaw here that requires deeper investigation; market sentiment is overly pessimistic," wrote Barclays analysts.

**The Half the Market Got Right: Application Layer Profit Squeeze** The market panic is not entirely unfounded. The application layer built on top of database infrastructure by SaaS companies has long underperformed: clunky interfaces, lack of intuitiveness, inflated prices, and sometimes security vulnerabilities. Worse, customers are often locked into inferior systems due to high migration costs.

Matt Stoller, Research Director at the American Economic Liberties Project, wrote, "The U.S. software industry model is built around monopolization, delivering low quality and poor security at high prices." He described a 2016 meeting with community bankers who lamented their niche software vendors as "expensive" and "terrible."

Swedish fintech company Klarna's decision in 2024 to stop using Salesforce and Workday software in favor of products from smaller SaaS firms like Deel and Neo4j, while using AI coding tool Cursor to build a more modern application layer on top, illustrates the true threat path of AI to SaaS. Customers are not simply replacing SaaS software with AI tools; they are using AI to build their own applications, squeezing out the expensive interface layer while retaining the underlying data.

**Repricing in the Software Sector Will Continue** This market correction is necessary for the enterprise software application layer. SaaS companies have long enjoyed high valuation multiples because they controlled both the infrastructure and the interface. If technology from Anthropic and OpenAI can overlay these systems of record, it will begin to erode the pricing power of SaaS companies.

The Barclays report concludes, "This implies the era of easy, high-margin profits for the bloated application layer of enterprise software is likely over." However, this is not equivalent to an apocalypse for the entire industry. The key is distinguishing which companies rely on application layer profits and which have their value rooted in the irreplaceable system of record layer.

Statements from SAP during its January earnings call reflect the confidence of system of record vendors. Other SaaS executives are also pushing back against bearish views. But the market needs time to digest these technical details and separate genuine disruptive threats from exaggerated fears.

The indiscriminate nature of the current sell-off suggests that investors, including those from credit markets who previously had limited understanding of the software sector, are making decisions based on the most extreme viewpoints.

As understanding deepens regarding the boundaries of AI capabilities and the business models of SaaS companies, the market may reprice those firms wrongly categorized as "AI victims." However, for companies that have long relied on inferior application layers to charge high fees, the valuation squeeze may have only just begun.