AI-Native Firms [pdf]
This paper introduces "AI-native firms"—organizations built around AI as a core capability. It compares them to traditional companies adopting AI later, highlighting differences in strategy, structure, and performance.
Background
- This Harvard Business School working paper (2026) introduces the concept of "AI-native firms"—companies built from the start around AI, rather than legacy firms that bolt AI onto existing operations.
- Co-authored by Karim Lakhani (Harvard), Marco Iansiti (Harvard), and several others, the paper argues that AI-native firms achieve "zero-cost prediction, zero-cost orchestration, and zero-cost adaptation," giving them structural advantages over traditional incumbents.
- The authors contrast these with "AI-enhanced firms" (legacy companies that add AI incrementally) and show how AI-native companies concentrate value creation in a single, continuously learning model rather than in people or static processes.
- Key examples cited include Stripe (payments), Anduril (defense), and Jasper (marketing AI). The paper uses formal modeling and case studies to predict that AI-native firms will capture disproportionate market share in the coming decade.
- Why it matters: The paper suggests a fundamental shift in competitive strategy—not just efficiency gains, but a new organizational form that may render traditional firms obsolete if they fail to transform at the architectural level.