AI will not disrupt the enterprise software ecosystem! Wedbush says the market reaction is overblown and strongly supports software companies like (MSFT.US), Salesforce(CRM.US), and others.

After Anthropic hosted its latest product launch event, Wedbush stated that market concerns about generative AI disrupting traditional enterprise software are significantly exaggerated, and recent software sector volatility is more driven by sentiment than fundamentals.

According to the analysis team led by Dan Ives at Wedbush, Anthropic showcased several enterprise-focused product updates at its “Enterprise Agents” launch event, highlighting agent-based workflows and enterprise-level integration capabilities. Through live demonstrations, Anthropic showed applications of Claude Cowork in multiple large companies, including Spotify Technology (SPOT.US) to shorten engineering time for complex code migrations, Novo Nordisk (NVO.US) to improve clinical research document organization efficiency, and Salesforce (CRM.US) to compress project cycles within Slack.

However, Ives emphasized that while these use cases are impressive, the next-generation AI tools will not “reinvent” or replace existing enterprise software ecosystems entirely. “The value of AI tools heavily depends on accessible data; they cannot operate independently outside existing systems,” he said. He pointed out that the market often equates foundational model capabilities with complete enterprise software platforms, overlooking the complex realities of enterprise IT environments.

Wedbush believes that foundational models are not equivalent to enterprise software platforms. The demonstrations by Anthropic and OpenAI mainly reflect the intelligence level of the models themselves, rather than the actual workflows, compliance and audit systems, security controls, system integration, billing mechanisms, and enterprise service level agreements that enterprises require. In contrast, vendors like Microsoft (MSFT.US), Salesforce, ServiceNow (NOW.US), and Pegasystems (PEGA.US) have deeply embedded into core enterprise processes, serving as the “system record layer.” Replacing them would mean reconstructing critical infrastructure, not simply overlaying a large model.

Analysts also noted that the proliferation of AI will increase system complexity, thereby raising cybersecurity expenditures. With the deployment of AI agents and automated workflows, API interfaces, machine identities, lateral movement risks, and cloud-native loads will significantly increase, boosting demand for endpoints, identity, cloud security, and security operations centers. As a result, security firms like CrowdStrike (CRWD.US), Palo Alto Networks (PANW.US), and Zscaler (ZS.US) are seen as beneficiaries of the AI era, not losers.

Regarding the competitive landscape, Wedbush believes that success in enterprise software still hinges on channels and customer relationships rather than just model performance. Anthropic and OpenAI lack extensive distribution networks or deep relationships with CIOs spanning decades, whereas Microsoft, Salesforce, and ServiceNow control the application layer where enterprise business logic resides. The analysts pointed out that accelerated AI adoption actually enhances the strategic value of these platforms, driving a new wave of system modernization rather than bypassing existing systems.

From a valuation perspective, Wedbush believes that the recent compression in software stock valuations does not align with future profit risks. There is no clear evidence of accelerated customer churn, budget freezes, or competitive replacements; the market is more reacting to “demo risks” rather than “data risks.”

Specifically, Wedbush sees the market’s concerns about Microsoft as exaggerated, presenting a significant opportunity for strategic positioning. At the same time, the analysts noted that IBM’s (IBM.US) stock decline lacks fundamental support. IBM remains deeply involved in operating numerous critical mainframe systems based on COBOL. Even as AI accelerates code migration and modernization, enterprises still require systematic migration, compliance validation, and integration services—areas where IBM has long-standing advantages and commercial expertise.

In summary, Wedbush concludes that AI is more likely to trigger a cycle of enterprise IT modernization rather than overthrow the existing software landscape. As AI reduces the friction costs of system upgrades, it will instead reinforce the long-term value of mainstream enterprise software platforms.