AI will not disrupt the enterprise software ecosystem! Wedbush believes that the market's reaction is exaggerated in support of software companies such as Microsoft Corporation (MSFT.US) and Salesforce, Inc. (CRM.US)

After the latest product launch event held by Anthropic, Wedbush stated that the market's concerns about the impact of generative artificial intelligence on traditional enterprise software have been significantly exaggerated, and the recent volatility in the software sector is more driven by emotions rather than fundamentals. Wedbush, led by analyst team Dan Ives, pointed out that Anthropic showcased multiple product updates aimed at enterprises during its "Enterprise Agents" launch event, highlighting agent-based workflows and enterprise integration capabilities. Through live demonstrations, Anthropic showcased the applications of Claude Cowork in various large enterprises, including Spotify Technology, Novo Nordisk A/S Sponsored ADR Class B, and Salesforce, Inc. compressing project cycles in Slack. However, Ives emphasized that despite the impressive use cases, the new generation of AI tools will not completely replace existing enterprise software ecosystems. He pointed out that the value of AI tools highly depends on the data they can access and they cannot operate independently of existing systems. He noted that the market often equates basic model capabilities with complete enterprise software platforms, overlooking the complexity of enterprise IT environments. Wedbush believes that basic models do not equate to enterprise software platforms. The demonstrations by Anthropic and OpenAI mostly reflect the intelligence level of the models themselves rather than the workflows, compliance and auditing systems, security controls, system integrations, billing mechanisms, and enterprise-level service level agreements truly needed by enterprises. In comparison, companies like Microsoft Corporation, Salesforce, Inc., ServiceNow, and Pegasystems have already deeply embedded themselves in core enterprise processes, acting as the "system record layer," replacing them would require restructuring critical infrastructure, rather than simply adding a large model. Analysts also pointed out that the proliferation of AI will actually increase system complexity, leading to higher cybersecurity expenditures. As AI agents and automated workflows are deployed, API interfaces, machine identities, lateral movement risks, and cloud-native workloads significantly increase, driving the demand for endpoint, identity, cloud security, and security operations centers. Therefore, security vendors such as CrowdStrike, Palo Alto Networks, and Zscaler are seen as beneficiaries of the AI era rather than losers. In terms of competitive landscape, Wedbush believes that the key to success in the enterprise software field still lies in channels and customer relationships rather than just model performance. Anthropic and OpenAI do not have the coverage of a twenty-year enterprise distribution network or strong relationships with chief information officers, while Microsoft Corporation, Salesforce, Inc., and ServiceNow control the application layer, where the logic of enterprise business resides. Analysts indicate that the acceleration of AI applications actually increases the strategic value of these platforms, driving enterprises to a new round of system modernization rather than bypassing existing systems. From a valuation standpoint, Wedbush believes that the recent compression in software stock valuations is not commensurate with future profit risks. There is currently no evidence of accelerated customer churn, budget freezes, or competitive replacements; the market is reacting more to "demonstration risk" than "data risk." Specifically, Wedbush believes that the market's concerns about Microsoft Corporation are exaggerated, presenting an important investment opportunity. At the same time, analysts also pointed out that the price drop of IBM Corp lacks fundamental support. IBM still deeply engages in and operates many critical mainframe systems based on COBOL. Even as AI accelerates code migration and modernization processes, enterprises still need systematic migration, compliance verification, and integration services, areas in which IBM has long had advantages and commercialized. In conclusion, Wedbush stated that AI is more likely to trigger a modernization cycle in enterprise IT rather than disrupt the existing software landscape. As AI lowers the frictional costs of transforming traditional systems, it reinforces the long-term value of mainstream enterprise software platforms.