Unlike cloud or mobile, which incumbents initially ignored, AI adoption is consensus. Startups can't rely on incumbents being slow. The new 'white space' for disruption exists in niche markets large companies still deem too small to enter.

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.

Instead of fighting incumbents for their entrenched "hostage" customers, startups should focus on "Greenfield Bingo." This strategy involves building a better product and selling it to the steady stream of new companies that are not yet locked into a solution. This approach thrives in markets with high rates of new business formation.

Founders are stuck in a SaaS mindset, selling tools to existing service providers. The bigger opportunity is to build new, AI-first service companies (e.g., accounting, legal) that use AI to deliver a superior end-to-end solution directly to customers.

Instead of trying to steal entrenched 'hostage' customers from incumbents, startups should focus on a 'Greenfield' strategy. By building a superior product, they can capture the wave of new companies that are not yet locked into a legacy system and will choose the best available solution.

Large incumbents struggle to serve newly-formed startups because these customers offer low initial revenue but require significant sales and support. This P&L constraint creates a protected 'greenfield' market for new vendors to capture customers early and grow with them.

For incumbent software companies, an existing customer base is a double-edged sword. While it provides a distribution channel for new AI products, it also acts as "cement shoes." The technical debt and feature obligations to thousands of pre-AI customers can consume all engineering resources, preventing them from competing effectively with nimble, AI-native startups.

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.