Industries with historically low software adoption (like trial law or dentistry) are now viable markets. Instead of selling a tool, AI startups are selling an outcome—the automation of a specific labor role. This shifts the value proposition from a software expense to a direct labor cost replacement.

AI enables "software does labor" business models in industries previously deemed too small for specialized software, like dental offices or trial law. By replacing or augmenting specific labor tasks, startups can justify high-value contracts in markets that historically wouldn't pay for traditional SaaS tools.

Many B2B companies failed by launching AI "co-pilots" that were too expensive for the minimal value they provided. The winning strategy, exemplified by Notion, is to create an AI add-on so valuable that users willingly pay a 50-100% premium, which in turn re-accelerates the company's growth.

Traditional SaaS companies are trapped by their per-seat pricing model. Their own AI agents, if successful, would reduce the number of human seats needed, cannibalizing their core revenue. AI-native startups exploit this by using value-based pricing (e.g., tasks completed), aligning their success with customer automation goals.

The high price point for professional AI tools is justified by their ability to tackle complex, high-value business tasks, not just minor productivity gains. The return on investment comes from replacing expensive and time-consuming work, like developing a data-driven growth strategy, in minutes.

Successful AI products like Gamma and Cursor don't just add a feature; they create so much value they can charge orders of magnitude more than legacy alternatives. This massive Total Addressable Market (TAM) expansion, not a simple price bump, is the engine of their explosive growth.

The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.

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.

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.