As SaaS firms use AI to optimize operations, they feed models data on how their products are built. This creates a deflationary spiral where customers can use the same AI to build cheaper alternatives, threatening the core SaaS business model by accelerating price and profitability compression.

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.

The "SaaSpocalypse" isn't about current revenues but a collapse in investor confidence. AI introduces profound uncertainty about future cash flows, causing the market to heavily discount what was once seen as bond-like predictability. SaaS firms must now actively prove they are beneficiaries of AI to regain their premium valuations.

The biggest threat to incumbent software companies isn't a new feature, but a business model shift. AI enables outcome-based pricing, which massively favors agile newcomers as incumbents struggle to adapt their entire commercial structure away from seat-based subscriptions.

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.

As AI commoditizes software creation and data migration, the high-margin, sticky nature of SaaS will disappear. Klarna's CEO predicts that valuations will compress from historical 20-30x price-to-sales multiples down to 1-2x, similar to how low-moat utility companies are valued.

The primary threat of Large Language Models to the SaaS industry isn't that they will build better software, but that they will enable the creation of 50 to 100 competitors for every existing player. This massive increase in competition will inevitably compress profit margins for everyone.

The market's downturn in legacy SaaS isn't primarily about AI automating jobs within those companies. The core fear is that new competitors can now use AI to build feature-complete products at a fraction of the cost, creating intense pricing pressure and margin compression for incumbents.