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.

Startups often fail to displace incumbents because they become successful 'point solutions' and get acquired. The harder path to a much larger outcome is to build the entire integrated stack from the start, but initially serve a simpler, down-market customer segment before moving up.

To overcome resistance from conservative real estate owners, Metropolis leased its first locations. This allowed them to deploy their technology, gather performance data, and prove the model's value on their own dime, removing the risk for potential partners.

Incumbents are disincentivized from creating cheaper, superior products that would cannibalize existing high-margin revenue streams. Organizational silos also hinder the creation of blended solutions that cross traditional product lines, creating opportunities for startups to innovate in the gaps.

Real estate owners were skeptical of new tech. Instead of focusing on operational cost savings, Metropolis's go-to-market strategy centered on proving they could capture more revenue by eliminating leakage (e.g., when gates are up), which directly increased the underlying value of the real estate asset.

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.

AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.

When selling their tech to risk-averse real estate owners proved too slow, Metropolis pivoted to a "Growth Buyout" strategy. They acquired a traditional parking operator, giving them immediate access to hundreds of locations to deploy their technology and accelerate their go-to-market.

New technology like AI doesn't automatically displace incumbents. Established players like DoorDash and Google successfully defend their turf by leveraging deep-rooted network effects (e.g., restaurant relationships, user habits). They can adopt or build competing tech, while challengers struggle to replicate the established ecosystem.