---
title: "Are We Entering a New Era of Job Instability Due to AI?"
author: "Tyler Maddox"
date: "2025-09-16"
updated: "2026-03-12T10:56:46-07:00"
canonical: "https://recursive.institute/articles/are-we-entering-a-new-era-of-job-instability-due-to-ai/"
license: "All rights reserved"
citation: "Tyler Maddox, \"Are We Entering a New Era of Job Instability Due to AI?\", 2025-09-16. https://recursive.institute/articles/are-we-entering-a-new-era-of-job-instability-due-to-ai/"
---

The relationship between artificial intelligence introduction and job market churn reveals a fascinating story of labor market stability disrupted by technological advancement. Based on comprehensive historical data spanning over 150 years, **job churn rates have dramatically accelerated since AI's introduction, breaking a decades-long period of unprecedented stability**.<sup>1</sup><sup>,</sup><sup>2,3</sup>

**The Pre-AI Era: Unprecedented Stability (1990-2019)**

Contrary to popular narratives about [rapid technological disruption](/2025/09/26/the-unseen-engine-navigating-the-maintenance-paradox-and-the-myth-of-perfection-in-the-l-a-c-economy/), the period from 1990 to 2017 represented **the most stable period in U.S. labor market history, going back nearly 150 years**. This era of stability was characterized by:<sup>1,4,2</sup>

**Historically Low Churn Rates**: Occupational churn during the 1990s and 2010s ranked among the least volatile periods since 1880. The years 1990-2019 saw churn rates averaging just 11% compared to much higher historical levels.<sup>1,3,1</sup><sup>[↗](https://www.nber.org/system/files/working_papers/w33323/w33323.pdf)</sup>

| Period | Churn\_Rate | Description | Era |
| --- | --- | --- | --- |
| 1880-1900 | 35.0 | Agriculture to industry transition | Pre-Industrial |
| 1900-1920 | 25.0 | Early industrialization | Early Industrial |
| 1920-1940 | 20.0 | Manufacturing growth | Industrial |
| 1940-1970 | 40.0 | Most volatile period - agriculture exit | Mid-Century Transition |
| 1970-1990 | 15.0 | Relative stability begins | Stabilization |
| 1990-2010 | 12.0 | Most stable period in 150 years | Pre-AI Stability |
| 2010-2019 | 10.0 | Continued stability, low disruption | Pre-AI Stability |
| 2020-2025 | 18.0 | AI-driven acceleration begins | AI Era |

**Gradual Decline in Turnover**: Employee quit rates from the Bureau of Labor Statistics show a steady pattern from 2000-2019, with the pre-AI average quit rate at 1.94%.

| Year | Quit\_Rate | Era |
| --- | --- | --- |
| 2000 | 2.0 | Pre-AI |
| 2005 | 1.8 | Pre-AI |
| 2010 | 1.5 | Pre-AI |
| 2015 | 2.0 | Pre-AI |
| 2019 | 2.4 | Pre-AI Peak |
| 2020 | 2.1 | Early AI/Pandemic |
| 2021 | 2.7 | Great Resignation/AI |
| 2022 | 2.8 | AI Era |
| 2023 | 2.4 | AI Era |
| 2024 | 2.1 | AI Era |
| 2025 | 2.0 | AI Era |

Even the 2019 peak of 2.4% - which set records at the time - represented organic economic growth rather than technological disruption.<sup>5,6</sup>

**Contradicting Automation Anxiety**: This period of stability occurred despite widespread fears about robots and [automation destroying jobs](/2025/11/21/the-automation-trap-why-every-efficiency-gain-eventually-consumes-itself/). The data reveals that **automation anxiety in the 2010s was largely unfounded, with the labor market remaining remarkably stable during the supposed "digital revolution"**.<sup>1,7,3</sup>

Historical Job Market Churn Rates: 150 Years of Labor Market Disruption

## The AI Era Acceleration (2020-2025) {#the-ai-era-acceleration-2020-2025}

The introduction and widespread adoption of artificial intelligence has fundamentally altered this pattern of stability, with **churn rates increasing by 63.6% compared to the pre-AI period**:

**Occupational Churn Surge**: The 2020-2025 period shows churn rates of 18%, representing a dramatic departure from the 10% rate of 2010-2019. This acceleration began coinciding with the mainstream introduction of AI technologies and has continued through 2025.<sup>1,4</sup>

**Quit Rate Acceleration**: Employee quit rates averaged 2.35% during the AI era (2020-2025), representing a **21.1% increase over pre-AI levels**. The peak occurred during 2021-2022 at 2.7-2.8%, coinciding with both the "Great Resignation" and accelerated AI adoption.<sup>8,9,10</sup>

**Sector-Specific Impacts**: AI is driving targeted disruption in specific occupations. Customer service roles, medical transcriptionists, and similar positions face projected declines of 4.7-5.0% through 2033. Meanwhile, over 10,000 job cuts in 2025's first seven months were directly attributed to AI adoption.<sup>11,8</sup>

Employee Quit Rates 2000-2025: The Impact of AI on Job Turnover

## Historical Context: Why This Time Is Different {#historical-context-why-this-time-is-different}

**Comparing to Past Disruptions**: The 1940-1970 period previously held the record for labor market volatility with churn rates of 40%, driven by agricultural transformation and post-war industrial shifts. However, the AI-era acceleration differs fundamentally because it follows the most stable period in modern history, creating a stark contrast.<sup>3,12</sup>

**Speed of Change**: Unlike previous technological disruptions that unfolded over decades, **AI compression may accelerate historical job turnover patterns into shorter timeframes**. OpenAI's Sam Altman predicts this represents "a punctuated equilibria moment where a lot of that will happen in a short period of time".<sup>13</sup>

**Cognitive vs. Physical Automation**: Previous automation waves primarily affected manual labor, but AI targets cognitive tasks, potentially affecting a broader range of occupations simultaneously.<sup>14,15,11</sup>

**The Great Resignation and AI Intersection**

The period 2021-2022 represents a unique confluence where **AI anxiety and pandemic-driven reevaluation created perfect storm conditions**:<sup>16,17,18</sup>

**AI as [Career Catalyst](/)**: Rather than simply causing job displacement, 76% of employees believe AI will help their career development and earning potential. This optimism is driving proactive job changes as [workers seek AI-enhanced roles](/2025/12/05/the-human-free-firm-why-full-automation-hits-a-wall/).<sup>19</sup>

**Volume Surge**: Voluntary turnover reached 50.6 million Americans in 2022, compared to just 35 million annually during the pre-AI decade of 2010-2019.

| Period | Avg\_Turnover | Volume\_Millions | Era |
| --- | --- | --- | --- |
| 2010-2019 | 15.5 | 35.0 | Pre-AI |
| 2020 | 21.0 | 42.0 | Pandemic/Early AI |
| 2021 | 27.0 | 50.0 | Great Resignation |
| 2022 | 28.0 | 50.6 | AI Era |
| 2023 | 24.0 | 45.0 | AI Era |
| 2024 | 21.0 | 42.0 | AI Era |
| 2025 | 20.0 | 40.0 | AI Era |

This represents a **44% increase in turnover volume**.<sup>20,21</sup>

**Future Predictions**: PwC's 2024 survey indicates 28% of workers are likely to leave their current company within 12 months, compared to 19% in 2022, suggesting continued elevation above historical norms.<sup>19</sup>

**Key Findings and Implications**

**Acceleration Confirmed**: Job churn has demonstrably accelerated since AI introduction, with both occupational churn (+63.6%) and quit rates (+21.1%) showing significant increases over pre-AI baselines.

**Breaking Historical Patterns**: The 2020-2025 period breaks a 30-year trend of [declining labor market volatility](/2025/09/04/the-end-of-labor-an-economic-analysis-of-automation-production-and-the-future-of-work/), suggesting AI represents a genuine technological inflection point rather than gradual evolution.<sup>1,3</sup>

**Sector Variability**: While overall churn has increased, impacts vary significantly by industry, with AI-exposed sectors like customer service, finance, and technology experiencing disproportionate effects.<sup>8,15,11</sup>

The data conclusively shows that AI introduction has **accelerated job churn rates after decades of unprecedented stability**. This acceleration appears to be continuing as AI capabilities expand and adoption deepens across industries, suggesting we may be in the early stages of a prolonged period of elevated labor market disruption compared to the remarkably stable pre-AI era.

⁂

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