More than half of Americans express concern that they or someone in their household could lose a job to artificial intelligence, according to a recent Reuters/Ipsos poll. While apprehension about AI-related job displacement is widespread, opinions across surveys vary, with some suggesting a more optimistic outlook on AI’s impact on employment.

In response to the evolving labor market dynamics, California has launched an ambitious new tool to track AI-related unemployment claims in near real-time. Developed by the California Policy Lab in collaboration with the state’s Employment Development Department, this public dashboard aims to provide more timely data on job losses attributed to AI exposure. The initiative joins existing efforts such as the Stanford Digital Economy Lab dashboard in enhancing the analytic resources available to economists and policymakers.

Researchers involved in the project acknowledge the limitations of the tracker, emphasizing that it captures only one dimension of AI’s influence—specifically, job separations—while omitting aspects like job creation, worker retention, and productivity-driven hiring. Consequently, the dashboard may present an incomplete picture of AI’s overall impact on employment.

Another challenge stems from California’s use of the Dictionary of Occupational Titles, a federal classification system last fully updated in 1991, which lacks modern job categories such as data scientists and machine-learning engineers. To address this gap, researchers translate outdated occupation codes into contemporary measures of AI exposure, often averaging data across diverse roles that may vary significantly in how AI affects them.

The tracker has recorded an increase in unemployment claims among workers in AI-exposed occupations beginning in late 2022, a period coinciding with the emergence of ChatGPT and other generative AI technologies. However, disentangling the effects of AI from broader economic shifts is complicated by the simultaneous end of the pandemic-driven tech hiring boom. Major technology firms including Meta, Google, Amazon, and Salesforce announced substantial layoffs in late 2022 amid rising interest rates, disproportionately affecting occupations more susceptible to AI disruption.

Experts caution that even if all rising unemployment claims were due to AI, the data still fail to capture the subsequent employment outcomes for displaced workers. Research conducted by economist Andrew Johnston and Christos A. Makridis using comprehensive U.S. employment data through 2024 found that industries with higher AI exposure have experienced faster productivity growth, increased employment, and rising wages. Other studies have similarly detected limited broad labor-market disruption from large language models.

Further evidence from company spending analyses indicates that firms investing heavily in AI have expanded their employment at a faster pace than comparable companies with lower AI investment.

While there is debate among researchers about the scale of AI’s labor market effects, emerging evidence suggests a pattern similar to previous technological revolutions: certain jobs are eliminated, many roles evolve, and new opportunities arise alongside productivity improvements. Critics of the current tracker argue that a sole focus on layoffs overlooks the full scope of these developments.

Reflecting on historical parallels, experts note that early 20th-century tools capturing job losses from automotive innovation would have failed to recognize the new employment generated in related industries such as mechanics and infrastructure.

California’s current AI job-loss dashboard represents a significant step in labor market measurement. Observers suggest the state should build upon this foundation by creating a complementary “AI opportunity tracker” to monitor job creation and growth, providing workers and policymakers with a more balanced understanding of AI’s labor market implications.