A proliferation of Artificial Intelligence (AI) applications specific to landscape architecture has revealed potential disruptions to many aspects of the professional design process, including tasks that require creative skills but are very time-consuming. Creating 2D assets for design renderings is an example of one such task, requiring an inordinate amount of time to create just a few image cut-outs with little customization. Generative AI art tools offer the possibility to both reduce production time and improve the quality and customizability of asset libraries. In this paper, we present a comparative assessment of three image generators’ (Dall-E 2, Midjourney, and Stable Diffusion) abilities to produce 2D asset libraries. The analysis includes the strengths and weaknesses of each generator in accuracy, usability, and artistic style. Recommendations for potential prompts and workflows to achieve desired results with each generator are also provided, along with a reflection on the greater implications of generative AI for landscape practice.