Established SaaS firms avoid AI-native products because they operate at lower gross margins (e.g., 40%) compared to traditional software (80%+). This parallels brick-and-mortar retail's fatal hesitation with e-commerce, creating an opportunity for AI-native startups to capture the market by embracing different unit economics.

The economic incentive for VCs funding AI is replacing human labor, a $13 trillion market in the US alone. This dwarfs the $300 billion SaaS market, revealing the ultimate goal is automating knowledge work, not just building software.

The narrative of AI destroying jobs misses a key point: AI allows companies to 'hire software for a dollar' for tasks that were never economical to assign to humans. This will unlock new services and expand the economy, creating demand in areas that previously didn't exist.

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.

Thrive Capital invested in an AI-powered accounting firm, not an accounting AI software tool. Their thesis is that in some industries, the service provider who uses AI to become hyper-efficient will capture more value than software vendors selling tools to a fragmented customer base. This is a bet on the business model, not just the technology.

Businesses previously considered non-venture scale due to service-based models and low margins, like Managed Service Providers (MSPs), are becoming investable. By building with an AI-first core, these companies can achieve the high margins and scalability required for venture returns, blurring the line between service and product.

Previously, building 'just a feature' was a flawed strategy. Now, an AI feature that replaces a human role (e.g., a receptionist) can command a high enough price to be a viable company wedge, even before it becomes a full product.

In a world where AI makes software cheap or free, the primary value shifts to specialized human expertise. Companies can monetize by using their software as a low-cost distribution channel to sell high-margin, high-ticket services that customers cannot easily replicate, like specialized security analysis.

Traditionally, service businesses lack scalability for VC. But AI startups are adopting a 'manual first, automate later' approach. They deliver high-touch services to gain traction, while simultaneously building AI to automate 90%+ of the work, eventually achieving software-like margins and growth.