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.

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.

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 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.

The fundamental business model of many SaaS companies is based on per-user pricing. AI agents pose an existential threat to this model by enabling smaller teams to achieve the same output as larger ones. As companies wonder why they should pay for 100 seats when 10 people can do the work, the entire economic foundation of the SaaS industry faces a crisis.

OpenAI Chair Bret Taylor argues that the biggest hurdle for established software companies isn't adopting AI technology, but disrupting their own business models. Moving from per-seat licenses to the outcome-based pricing that agents enable is a more profound and difficult challenge.

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.

The current market leaves no room for mediocrity. SaaS companies are either at the forefront of AI, delivering jaw-dropping value and capturing new budget, or they are being displaced. Hiding behind long-term contracts is a temporary solution, as there is no longer a middle ground.

To succeed in the AI era, SaaS companies cannot just add AI features. They must undergo a 'brutal' transformation, changing everything from their org chart and GTM strategy to their core metrics and pricing model. This is a non-negotiable, foundational shift.