The enterprise embrace of AI reflects a deeper desire to reduce headcount, not just adopt new technology. This structural shift away from hiring creates a sustained headwind for seat-based SaaS models, making it difficult to predict a bottom for their valuations.
The "SaaS-pocalypse" isn't about AI replacing software overnight. Instead, AI's disruptive potential erases the decades-long growth certainty that justified high SaaS valuations. Investors are punishing this newfound unpredictability of future cash flows, regardless of current performance.
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.
In categories like customer support, where AI can handle the vast majority of queries, charging per human agent ('per seat') no longer makes sense. The business model is shifting to be outcome-based, where customers pay for the value delivered, such as per ticket resolved or per successful interaction.
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.
The fundamental business model of many SaaS companies is based on per-user pricing. AI agents pose an existential threat to this model by enabling smaller teams to achieve the same output as larger ones. As companies wonder why they should pay for 100 seats when 10 people can do the work, the entire economic foundation of the SaaS industry faces a crisis.
The challenge for SaaS isn't simply adding an AI agent. Growth is attacked by shrinking workforces (seat contraction), CIO budgets shifting to AI, and aggressive price hikes that eliminate upsell opportunities. This combination makes returning to the high-growth, high-NRR days of the past unlikely.
The recent $300B SaaS stock sell-off wasn't driven by current performance. Investors are repricing stocks based on deep uncertainty about whether legacy software companies or AI-native firms will capture the value of automating human labor in the next 3-5 years.
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.
The push for AI-driven efficiency means many companies are past 'peak employee.' This creates a scenario analogous to a country with a declining population, where the total number of available seats is in permanent decline, making per-seat pricing a fundamentally flawed long-term business model.