We study the employment effects of different artificial intelligence (AI) adoption strategies. Using corporate disclosures from 2020 to 2025, we classify three types of AI adoption strategies: automation, augmentation, and reorganization. Following the large-scale diffusion of AI after the release of ChatGPT in November 2022, we document an overall decline in junior hiring relative to senior hiring. Yet, we find substantial heterogeneity across adoption strategies. Automation and reorganization are associated with declines in junior employment relative to senior employment, whereas augmentation is associated with the opposite pattern. These employment effects are driven primarily by reductions in hiring rather than increases in separations, and are concentrated in core positions rather than in support roles within the firm. At this early stage of adoption, AI is also associated with lower labor productivity but higher stock returns, consistent with short-run adjustment costs accompanied by investor expectations of longer-run efficiency gains. Overall, our results highlight that the labor market impact of AI depends critically on how firms choose to implement the technology, not merely on whether they adopt it.