In this episode of the ASAE Tech Insider podcast, Heather Harris, PhD, Founder and Principal Data Scientist at Herkimer Consulting, collaborates with Juan Sanchez, CIO at Inteleos, Denali Carpenter, Data Scientist at Inteleos, and moderator Carlos Cardenas, Senior Director of IT at NBCRNA and ASAE Tech Council Chair to discuss the pervasive challenge of missing data and its implications. The conversation centers around innovative strategies for addressing missing data, with a strong emphasis on the importance of data governance and quality in AI and machine learning applications. Dr. Harris introduces the topic by highlighting the impact that missing data can have on organizational analytics and the necessity for robust data handling methods. She and her colleagues describe how Inteleos employs advanced data imputation techniques, focusing on outcome-driven thinking and goal-setting to improve data accuracy and operational efficiency. The panel also underscores the significance of complete, high-quality datasets in training AI models, advocating for more sophisticated imputation methods beyond basic approaches like mean imputation. Additionally, the discussion extends to the application of imputation techniques for unstructured data and its potential to enhance AI development and performance.