In order to successfully implement AI technologies, organizations should have a solid foundation of clean, organized data. Data wrangling is a foundation of AI readiness that supports trustworthy, accurate, and useful data for AI development. Data wrangling can also identify potential risks in the data and mitigating them before AI development begins. By prioritizing data wrangling in AI readiness, organizations can take advantage of AI technologies to leverage efficiencies and scale operations. This webinar will touch on best practices for data cleaning, transformation, and consolidation, as well as provide tips for ensuring data quality and integrity. We will discuss the critical role of data wrangling in AI readiness and how it can help organizations mitigate risks associated with AI development. Attendees will gain insights into best practices for managing data in AI development and governance, including how to identify and mitigate bias, and ensure data privacy and security.