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.
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A market bifurcation is underway where investors prioritize AI startups with extreme growth rates over traditional SaaS companies. This creates a "changing of the guard," forcing established SaaS players to adopt AI aggressively or risk being devalued as legacy assets, while AI-native firms command premium valuations.
Unlike traditional SaaS where product-market fit meant a decade of stability, the rapid evolution of AI models makes today's PMF fleeting. Founders face the risk that their product could feel obsolete within a year, requiring constant innovation just to stay relevant in a rapidly changing market.
In the previous SaaS era, emulating giants like Salesforce was a common but flawed strategy for startups. In the new AI era, there is no playbook at all, forcing founders to rethink go-to-market strategies from first principles rather than copying incumbents.
The rapid evolution of AI means traditional private equity M&A timelines are too slow. PE firms and their portfolio companies must now behave more like venture capitalists, acquiring earlier-stage, riskier AI companies to secure necessary technology before it becomes unaffordable or obsolete.
AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.
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.
In the age of AI, 10-15 year old SaaS companies face an existential crisis. To stay relevant, they must be willing to make radical changes to culture and product, even if it threatens existing revenue. The alternative is becoming a legacy player as nimbler startups capture the market.
Recent acquisitions of slow-growth public SaaS companies are not just value grabs but turnaround plays. Acquirers believe these companies' distribution can be revitalized by injecting AI-native products, creating a path back to high growth and higher multiples.
The conventional wisdom for SaaS companies to find their 'second act' after reaching $100M in revenue is now obsolete. The extreme rate of change in the AI space forces companies to constantly reinvent themselves and refind product-market fit on a quarterly basis to survive.
The fundamental shift from AI isn't about replacing foundational model companies like OpenAI. Instead, AI creates a new technological substrate—productized intelligence—that will engender an entirely new breed of software companies, marking the end of the traditional SaaS playbook.
