This study explores the integration of Generative Artificial Intelligence (GenAI) tools into the design workflows of landscape architecture focusing on enhancing creativity, efficiency, and precision throughout the design process. Leveraging text-to-image and image-to-image generators (MidJourney 6, LookX) and hybrid methods with Adobe Photoshop Firefly and conventional methods such as sketching the research, embeds an exploratory experiment within a real-world landscape design case study. The tools were applied across five design phases: preliminary investigation, analysis, concept development, design refinement, and presentation. Key findings show that GenAI tools when combined with traditional methods such as manual sketching and GIS-based analysis significantly streamline early design phases by facilitating the generation of inspiration boards and concept visuals. MidJourney and LookX demonstrated potential for creating detailed renderings and rapid design variations, improving iterative workflows. However, AI’s limited spatial understanding and reliance on curated datasets pose challenges for generating project-specific technically accurate outputs. The study highlights GenAI’s capacity to enrich visual communication and amplify creative exploration. While GenAI tools cannot replace human expertise, their integration as complementary design aids fosters more dynamic and adaptive workflows. Future research will involve fine-tuning AI models using Low-Rank Adaptation (LoRa) to enhance their relevance to landscape architecture, addressing limitations in site-specific and context-aware content generation.