Deflationary shock on labor, starting with capital-labor substitution modeling. It emphasizes that employers need fewer professionals and the average labor market price falls toward the cost of the replacement machine. This is formalized via a CES production function augmented by AI, where K is capital (computing power, robots), L is labor, and H is AI-augmented human capital. Parameter ρ→0 implies perfect substitutability between K and L·H. The real wage (w) first-order condition shows that when H→∞ (powerful generative AI), w converges to the marginal cost of machine inference. A modified dynamic Fisher equation for labor shows wage deflation for white-collar workers when H˙/H > A˙/A. The automation diffusion timeline (2028-2033) follows a logistic curve with t0≈2029 (inflection point) and k≈0.8 (adoption speed). The WEF estimates 92 million net job destructions by 2030 (22% churn), while Goldman Sachs projects 9% of US workforce (~15 million) displaced over 10 years. The equilibrium unemployment rate (NAIRU) is revised upward, forcing central banks to choose between financial repression (inflation) and debt monetization. @SteelldyIndice