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Explore the critical gap between executive expectations and the reality of AI implementation in this 32-minute conference talk that addresses the fundamental challenge of data readiness in AI adoption. Discover why 90% of business leaders believe their data ecosystems are AI-ready while 84% of IT practitioners spend over an hour daily fixing data problems, and learn how to bridge this disconnect through comprehensive data preparation strategies. Examine the six key pillars of AI data readiness including infrastructure, integration, quality, governance, accessibility, and literacy, with practical assessment frameworks and implementation strategies for each component. Gain insights into the complete data readiness journey from collection to curation and governance, while understanding the distinction between efficiency-focused AI applications and higher-value, growth-oriented use cases that demand more sophisticated data foundations. Master practical techniques for conducting data readiness assessments, implementing gap remediation strategies, and establishing quantitative measurement approaches to track progress. Learn actionable strategies to transform your organization's data from a bottleneck into a strategic AI asset, ensuring both traditional and generative AI applications deliver meaningful business value regardless of whether you're beginning your AI journey or scaling existing initiatives.
