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Times Square Capital focuses its software investments on infrastructure (tied to consumption), cybersecurity, and vertical SaaS. They are wary of seat-based models (e.g., traditional CRM, HRIS) which may face headwinds if AI-driven productivity gains lead to slower enterprise headcount growth.
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.
SaaS companies are not equally vulnerable to AI. Some (like Zendesk) tie seats to work AI can replace. Others (like Workday) use seats as a proxy for company size and are safer. Markets are currently failing to differentiate, creating a valuation gap worth understanding.
Unlike mobile or cloud, which were sustaining innovations that enhanced existing SaaS models, AI is a disruptive force. It fundamentally challenges seat-based pricing and requires a difficult, full-stack pivot of a company's business model, culture, and organizational structure.
Sridhar Ramaswamy suggests software valuation multiples are contracting because investors see through the strategy of just adding an 'AI SKU.' The market believes this approach won't win, favoring integrated, consumption-based models where customers only pay for demonstrated value from AI.
The "SaaS apocalypse" will target "beta" software—tools that make companies more similar to their competitors. Conversely, "alpha" software—platforms that allow a company to express its unique strategy and competitive advantage—will thrive as AI makes customization and differentiation easier.
As large AI models absorb functions of traditional SaaS products, investors and entrepreneurs are shifting focus back to tech-enabled services. Integrating AI deeply into physical services and workflows is now seen as creating more defensible, lasting value than pure software, reversing a years-long trend.
Value in the AI stack will concentrate at the infrastructure layer (e.g., chips) and the horizontal application layer. The "middle layer" of vertical SaaS companies, whose value is primarily encoded business logic, is at risk of being commoditized by powerful, general AI agents.
AI doesn't kill all software; it bifurcates the market. Companies with strong moats like distribution, proprietary data, and enterprise lock-in will thrive by integrating AI. However, companies whose only advantage was their software code will be wiped out as AI makes the code itself a commodity. The moat is no longer the software.
A 'tale of two cities' exists in SaaS. Traditional software budgets are frozen, with spending eaten by price hikes from incumbents. Simultaneously, new, separate AI budgets are creating massive opportunities, making the market feel dead for classic SaaS but booming for AI-native solutions.
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.