Two strategic advantages that define success in the AI era

In the AI era, investors prioritize business models resistant to replication. A study of 576 venture-backed AI B2B companies found only two moats consistently deliver strong valuations. Counter-positioning, where a model is distinct enough that incumbents cannot copy it without harming their economics, commands a median enterprise value of 5.3x per dollar raised. Examples include vertically integrated AI insurers and AI-native revenue management systems. Network economies, where value increases with user growth, offer a 4.2x multiple. SC Moatti, founder of Mighty Capital, notes companies with these structural advantages outperform those relying on proprietary data or switching costs. Founders must ask: Could an incumbent copy their model? Those building moats that survive better-funded competitors command premium valuations. The study, using Crunchbase data and insights from Products That Count’s community, found 5% of companies leverage counter-positioning, while network economies appear in 5% of firms but deliver higher returns. Switching costs, though common, offer lower multiples due to high capital requirements. Scale economies are dominated by OpenAI and Anthropic, leaving little room for others. Moatti emphasizes the key to success lies in building something beneath the AI—a structural advantage a model cannot replicate. This distinction separates products from power, determining which startups can thrive in the AI-driven market.