The Institutional Window: Occupation- and Jurisdiction-Specific Calibration of Liability Signaling for Preserved Human Fallback Capability
Problem definition. When generative AI produces expert artifacts clients cannot distinguish from a competent provider's, the classical cost-based quality signal collapses and only outcome-contingent commitments can separate types. Such a commitment certifies an endogenous, perishable asset: the human fallback capability a firm builds by keeping staff engaged with cases the AI handles, eroding otherwise. Prior work is silent on where that mechanism holds. We ask where, across occupations and liability institutions, it remains informative. Methodology/results. We introduce an institutional wedge between the liability cap a firm posts and the retained exposure that carries information, generated by four legal primitives: the cost rule, the enforceability of penalty clauses, the displacement of private liability by state liability or pooled indemnity, and mandatory limits on contractual liability. The wedge compresses the separating type space into a signaling window, bounded above by solvency and the penalty doctrine and below where standard-terms control voids caps beneath a threshold. We calibrate five occupations and seven jurisdictions on published evidence. In common-law agreed-damages channels the provability gross-up is unavailable whenever verifiability falls below 1/m, turning a contracting problem into an operational one. Verifiability investment widens the window where the ceiling binds but narrows it where the cap floor binds. In an agent-based market, within the tested policy class, every empty-window cell converges to zero engagement and skill collapse. Managerial implications. Liability institutions are a workforce-capability instrument, not merely a risk-allocation device. Firms should target the binding margin in each jurisdiction; cap floors and pooled indemnity each suppress the signal sustaining fallback capacity.