In order to effectively implement AI within an organization, it's crucial to consider governance capabilities, tech stack, and data quality to tailor a plan according to readiness levels. This involves building strong processes in place for managing AI use, ensuring compliance with industry standards, and fostering cross-team collaboration. A connected tech stack is also essential, emphasizing interoperability, adaptability, and scalability. Moreover, high-quality data that's clean, organized, and accessible is vital, as poor data can lead to poor decision-making and ultimately worse business outcomes. By focusing on the three pillars of AI readiness - process, technology, and data - organizations can lay a strong foundation for AI success and reap its transformative benefits.