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.

Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.

Economist Bernd Hobart argues that large enterprises are too risk-averse for early AI adoption. The winning go-to-market strategy, similar to Stripe's, is for AI-native companies to sell to smaller, agile customers first. They can then grow with these customers, mature their product, and eventually sell the proven solution back to the legacy giants.

Most successful SaaS companies weren't built on new core tech, but by packaging existing tech (like databases or CRMs) into solutions for specific industries. AI is no different. The opportunity lies in unbundling a general tool like ChatGPT and rebundling its capabilities into vertical-specific products.

Counter to fears that foundation models will obsolete all apps, AI startups can build defensible businesses by embedding AI into unique workflows, owning the customer relationship, and creating network effects. This mirrors how top App Store apps succeeded despite Apple's platform dominance.

The true economic revolution from AI won't come from legacy companies using it as an "add-on." Instead, it will emerge over the next 20 years from new startups whose entire organizational structure and business model are built from the ground up around AI.

AI makes the technical 'doing' of business, like coding, accessible to everyone. The durable competitive edge is no longer the ability to build a product, but the ability to reach and acquire customers. Audience and distribution channels are the new defensible assets.

Incumbents face the innovator's dilemma; they can't afford to scrap existing infrastructure for AI. Startups can build "AI-native" from a clean sheet, creating a fundamental advantage that legacy players can't replicate by just bolting on features.

Most current AI tools are skeuomorphic—they just perform old tasks more efficiently. The real transformation will come from "AI-native" applications that create entirely new business models, just as Uber was an "iPhone-native" concept unimaginable before its time. The biggest winners will use AI to become the industry, not just sell to it.