How has AI impacted the labor market? Since generative AI was first introduced nearly three years ago, surveys show widespread public anxiety about AI’s potential for job losses. While it is impossible to accurately predict the future, we can examine how U.S. employment has changed since ChatGPT’s release in November 2022. Our analysis complements other recent studies that provide nascent evidence of possible AI impacts on specific occupations and sub-populations, such as early career workers. We took a broader lens, widening the aperture to the whole labor market, and asked two main questions. First, is the pace of labor market change in this 33-month period of employment disruption different from past periods of early technological change? Second, is there evidence of economy-wide employment effects? To answer these questions, we compare how quickly the occupational mix has changed across a range of measures since ChatGPT’s launch, and compare this to past disruptions from computers and the internet. Overall, our metrics indicate that the broader labor market has not experienced a discernible disruption since ChatGPT’s release 33 months ago, undercutting fears that AI automation is currently eroding the demand for cognitive labor across the economy.1 While this finding may contradict the most alarming headlines, it is not surprising given past precedents. Historically, widespread technological disruption in workplaces tends to occur over decades, rather than months or years. Computers didn’t become commonplace in offices until nearly a decade after their release to the public, and it took even longer for them to transform office workflows. Even if new AI technologies will go on to impact the labor market as much, or more, dramatically, it is reasonable to expect that widespread effects will take longer than 33 months to materialize. Of course, our analysis is not predictive of the future. We plan to continue monitoring these trends monthly to assess how AI’s job impacts might change. It is important to remember that the effects of new technologies are evolving and a simple snapshot in time is not enough to explicitly determine what the future holds.