Enterprises face significant challenges in achieving AI readiness due to underlying data readiness issues, as highlighted in a discussion with industry experts. Many organizations, despite being crucial to data and AI infrastructure, rate low on data maturity, which is a necessary precursor to AI maturity. Common obstacles include complex architectures, siloed data, and persistent infrastructure problems, which result in excessive time spent on pipeline maintenance rather than innovation. To overcome these hurdles, companies need a robust data foundation, enabling reliable data integration and governance, supported by platforms like Fivetran that automate data processes. Transitioning to cloud-based, centralized data platforms with features like AI-ready architecture and comprehensive data management can alleviate vendor lock-in risks while facilitating AI implementation. Starting small with meaningful AI projects can help organizations gradually build capacity and realize measurable business value, moving away from infrastructure maintenance to focus on operational efficiency and customer experience.