Software Commoditization in the AI-First Economy: From Implementation Moats to Contribution Markets

Abstract

AI-assisted software generation changes the economics of software scarcity. We argue that value does not disappear when recognizable interfaces and workflows become easier to reproduce. It moves toward assets and relationships that remain controlled, trusted, licensed, institutionally embedded, or agent-accessible. We develop five directional hypotheses. (1) Implementation moats can weaken for visible and evaluable patterns. (2) Defensibility shifts relatively toward complementary assets. (3) Access subscriptions face pressure when generic functionality is not bundled with trust, rights, compliance, or integration depth. (4) Governed service layers create new monetization options for agents. (5) Traceable contribution markets may route value to source assets and action endpoints when attribution, provenance, rights metadata, and payment rails are sufficient. Rather than treating commoditization as only a coding-productivity problem, we develop a multidisciplinary systems account that links software-engineering evidence, resource-based and information-systems strategy, intellectual-property scholarship, provenance and attribution methods, data economics, and agent-commerce infrastructure around one question: what remains scarce when implementation becomes easier to reproduce? We triangulate the argument with a qualitative case study of Myflix and recent descriptive market evidence. The contribution is integrative rather than a claim of universal proof: we connect existing theory to AI-assisted software reproduction and propose a bounded mechanism for moving from access monetization toward trusted capability, governed agent actions, and attributable contribution to generated outputs.