Abstract This chapter deals with the intersection of economics and technology and how they may shape the decision to adopt generative artificial intelligence (genAI). From the firm perspective, we discuss characteristics that make genAI different from past technologies, such as reduced changeover costs and reduced sensitivity to variability. We argue that, compared with past automation, these characteristics may spur adoption in tasks that are less frequent within an organization or more complex. We explore incentives for workers to adopt genAI: if genAI tends to augment less-skilled workers, workers with greater ability to critically evaluate the outputs of genAI may not have an incentive to adopt, which we propose could drive down the quality of genAI outputs and in the long-term, future models. Lastly, we describe how potential exposure to genAI may correlate across related occupations and could inform where disrupted workers find new employment and how occupations affected by genAI may transform.