THE STRUCTURAL FLAW Why the Industrial Labor Contract Cannot Regulate Post-Industrial Knowledge Work — and Why Agentic AI Has Made the Problem Unsustainable

ABSTRACT This paper identifies and theorizes a structural flaw in post-industrial labor markets: the standard employment contract—designed for industrial-era remuneration of time worked and universal assignment of intellectual property under the "work for hire" doctrine—is systematically inadequate for governing knowledge work. Three exogenous developments have rendered this institutional obsolescence unsustainable. First, algorithmic expropriation (AEI explains 56.1% of cross-occupational wage variance across 923 O*NET occupations) enables firms to codify workers' tacit knowledge into alienable algorithmic assets. Second, Agentic AI extends expropriation from knowledge codification to autonomous action, driving replacement costs toward zero. Third, Quantitative Easing (2008–2024) compressed real interest rates near zero, transforming senior workers' future wages into maximized liabilities absent corresponding intellectual capital assets on corporate balance sheets. Exploiting pre-crisis debt maturity structures across 82 publicly listed firms (2005–2024), we estimate that top-quartile QE-exposure firms increased early retirement scheme probability by 4.2 percentage points (48% relative to baseline). Each displaced senior worker generates negative fiscal externalities estimated at €142,000 net present value over ten years. The analysis is supported by the ITEA Framework v1.45 (García-Lluis Valencia, 2026), a multidimensional index covering 1,016 occupations across eight complementary indicators of automation and algorithmic exposure. The paper concludes by sketching a new institutional architecture for knowledge work: a hybrid contract combining base wages, intellectual capital royalties continuing beyond employment, and tokenized labor debt, alongside governance frameworks for Agentic AI (traceability, human override, right to explanation, periodic audit, fitness-for-purpose certification). Keywords: Algorithmic expropriation, Knowledge worker, Agentic AI, Quantitative Easing, Labor contract, Insider-Outsider, Early retirement, Fiscal externalities, ITEA JEL Codes: E52, E58, J26, J63, J24, G32, H55, K31