Permira's analysis suggests AI can replicate software features, eroding the value of high switching costs and recurring revenue. The new moat is whether a company owns critical data or is deeply embedded in workflows.

MongoDB's CEO argues that AI's disruptive threat to enterprise software is segmented. Companies serving SMBs are most at risk because their products are less sticky and more easily replaced by AI-generated tools. In contrast, vendors serving large enterprises are more protected because "products are always replaceable, platforms are not."

Goldman's CIO suggests a software vendor's vulnerability to AI depends on whether its core business process will be transformed. Regulated processes like accounting are safe, while dynamic areas like the software development lifecycle are highly susceptible to disruption.

Pure software-as-a-service (SaaS) companies are vulnerable to being replaced by foundational AI models that can replicate their functionality. A Sequoia partner suggests the defensible model is to become a services company that uses technology as a layer, focusing on implementation, strategy, and human expertise.

The "SaaS apocalypse" will target "beta" software—tools that make companies more similar to their competitors. Conversely, "alpha" software—platforms that allow a company to express its unique strategy and competitive advantage—will thrive as AI makes customization and differentiation easier.

Software's main competitive advantage isn't code, but its deep integration into customer data and workflows, creating high switching costs. AI threatens this moat by automating those integrated tasks, reducing customer stickiness and pricing power.

The core value of CRM software like Salesforce has been to structure unstructured sales data via manual human input. Modern AI can now ingest sources like meeting transcripts and automatically populate a database, threatening the entire CRM software category and the data entry aspect of sales roles.

Not all software is equally threatened by AI. Companies whose products are integral to creating proprietary, transactional data (like court case filings) have a strong defense. Their value is in the data and compliance layers, unlike UI-focused tools which are more easily replicated by AI agents.

The fear that AI agents will kill SaaS is overblown. Corporations will not replace mission-critical, supported software with AI-generated code from junior employees. The need for vendor accountability, reliability, and support creates a durable moat for enterprise software companies.