Recent advances in generative artificial intelligence have generated considerable optimism about its potential to increase productivity, improve services, and change how work is performed, while also raising concerns about privacy, bias, job displacement, and the broader consequences of advanced AI. This paper asks: How should we understand the current AI transition in the context of earlier technological transformations? To address that question, the paper combines historical perspective and a synthesis of the automation and AI literature with a new analysis of nationally representative data from the 2025 Survey of Household Economics and Decisionmaking (SHED) and qualitative evidence from the 2026 Federal Reserve System Worker Perspectives Project. These sources distinguish technological capability and occupational exposure from actual workplace adoption and worker experience. Descriptive comparisons and multivariate analysis show substantial variation in generative AI use, with economic and educational characteristics being particularly important. Among users, perceptions are generally favorable regarding AI’s usefulness for work, although concerns about employment remain. The findings suggest that generative AI is consequential, but its diffusion and effects remain uneven across workers and workplaces.