A significant, often unspoken, value of third-party software is accountability. When a critical system like an open-source database fails, companies need a vendor to call for support and to bear responsibility, a crucial 'cover your ass' function.
AI can generate code, but the real value of enterprise software is its integration into complex human workflows, the massive costs of change management, and network effects. These human-centric problems create a durable moat that code generation alone cannot overcome.
The current SaaS sell-off isn't driven by poor performance—growth and retention are stable. Instead, investors are pricing in a long-term, existential 'cliff risk' that AI will eventually make entire categories of software and knowledge work obsolete.
A key reason users stick with products like Zoom, despite free alternatives, is 'herd familiarity.' The entire ecosystem knows the software, reducing training friction and onboarding time. This collective knowledge is a significant competitive advantage that is difficult for new entrants to replicate.
While enterprises might leverage AI to build custom in-house solutions, SMBs are highly resistant to the pain of switching core systems like point-of-sale. This inertia makes niche SaaS for SMBs more defensible against the immediate threat of AI-driven replacement.
Unlike with consumer brands, most investors have never used complex enterprise software like Veeva. This lack of product intuition means they rely on financial tables and narratives, making the sector highly susceptible to panic-selling during crises like the 'SaaSpocalypse'.
AI can easily write code for system integrations, but the primary bottleneck isn't coding—it's context. The real work involves tracking down employees to understand what ambiguous, legacy data fields actually mean, a fundamentally human task of institutional knowledge discovery.
Widespread use of non-GAAP metrics that exclude stock-based compensation (SBC) creates a misleading picture of profitability. In reality, many SaaS firms have minimal GAAP earnings, meaning there's no fundamental 'floor' for value investors to step in and buy during a market panic.
AI tools aren't just making employees more efficient; they are replacing human labor. This allows software companies to move from cheap per-seat pricing to a new model based on outcomes, like charging per support ticket resolved, capturing a much larger share of the value.