Artificial intelligence (AI), and especially generative AI tools, have become more prevalent in recent years and increasingly challenge our world to rethink how written and design work is created. As this technology has evolved, generative AI tools are now capable of generating a plethora of written work, video content, photographs, visual images, and much more. As societal trends have shifted toward an increasing reliance and support for visual content (Makrydakis, 2024), there is a greater demand to create visual content quickly, and generative AI tools offer a solution to those who may lack training or skill in visual communication development. However, as many users of these tools have learned, the results generated can often be inaccurate or questionable. Research with agricultural communications students has found students have favorable views of the use of generative AI tools and feel that these tools are capable of producing images that accurately portray agricultural topics. This research suggested that users of generative AI tools run text-based prompts or cues through another AI tool, such as Chat-GPT, to generate language that AI can better understand to enhance the accuracy or level of detail provided in generated images. This has been tested in an undergraduate agricultural communications course to determine the impact AI-generated language has on the perceived accuracy of images generated. Teaching and encouraging this best practice to students has improved the perceived quality and accuracy of AI-generated images in this course. Many lessons and improved applications have been learned as a result of this practice in this course and will be shared during this presentation. Generating more accurate portrayals of agricultural topics is an important step in helping combat the increasingly questioned practices of the industry and may lead to greater transparency and trust from the public.