Toward a Bad Job Economy: AI Adoption, Agency Costs, and Job Design

We study how AI affects compensation and job design when performance depends on workers' non-contractible effort. In a principal–agent model with limited liability, AI reduces effort costs but disproportionately lowers the cost of achieving satisfactory performance. This raises the incentive cost of sustaining high effort and can induce firms to replace high-wage, high-effort good jobs with low-wage, low-effort bad jobs, even when good jobs create more total surplus. As a result, AI can lower wages, reduce worker welfare, and even depress profits. If workers can adopt AI unilaterally, adoption occurs even when the resulting equilibrium harms both parties; when adoption requires worker cooperation, resistance is strongest where AI erodes rents embodied in good jobs. In a search-and-matching extension, endogenous outside options amplify these forces, reinforcing a bad-job economy and potentially reducing employment.