The downturn in software stocks isn't tied to current earnings. Instead, investors are repricing the entire sector, removing the premium they once paid for its perceived safety and stable, long-term contracts, which are now threatened by AI disruption.
Software, once a defensive haven for credit investors, faces a major threat from AI. AI's ability to standardize data and workflows could disrupt legacy SaaS companies, making the 30% of direct lending portfolios concentrated in software a significant, overlooked risk.
Private equity firms, which heavily invested in software companies for their stable earnings, are now in a bind. The AI threat devalues these assets and complicates exits, forcing them away from traditional IPOs and toward more complex M&A strategies.
While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.
AI's ability to generate software at near-zero marginal cost is erasing the scarcity premium that propelled software stocks for over a decade. This realization is causing a massive capital rotation out of software ETFs and into tangible, scarce assets like metals and commodities.
Initially viewed as a growth driver, Generative AI is now seen by investors as a major disruption risk. This sentiment shift is driven by the visible, massive investments in AI infrastructure without corresponding revenue growth appearing in established enterprise sectors, causing a focus on potential downside instead of upside.
The long-held belief that a complex codebase provides a durable competitive advantage is becoming obsolete due to AI. As software becomes easier to replicate, defensibility shifts away from the technology itself and back toward classic business moats like network effects, brand reputation, and deep industry integration.
AI is making core software functionality nearly free, creating an existential crisis for traditional SaaS companies. The old model of 90%+ gross margins is disappearing. The future will be dominated by a few large AI players with lower margins, alongside a strategic shift towards monetizing high-value services.
For over a decade, SaaS products remained relatively unchanged, allowing PE firms to acquire them and profit from high NRR. AI destroys this model. The rate of product change is now unprecedented, meaning products can't be static, introducing a technology risk that PE models are not built for.
The lucrative maintenance and migration revenue streams for enterprise SaaS, which constitute up to 90% of software dollars, are under threat. AI agents and new systems are poised to aggressively shrink this market, severely impacting public SaaS companies' incremental revenue.
Sierra CEO Bret Taylor argues that transitioning from per-seat software licensing to value-based AI agents is a business model disruption, not just a technological one. Public companies struggle to navigate this shift as it creates a 'trough of despair' in quarterly earnings, threatening their core revenue before the new model matures.