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Guide

AI-Ready Data Essentials

Most AI initiatives fail not because of the AI itself but because of the data behind it. Incomplete records, inconsistent formats, siloed systems, and weak governance all prevent AI models from producing reliable outputs, and most organizations do not discover these gaps until they are already deep into deployment. This guide from Gartner defines the data readiness foundations that organizations need to put in place before they can realistically scale AI, covering data quality standards, access and lineage requirements, governance structures, and the technology infrastructure decisions that determine whether your AI investments generate lasting business value or require costly remediation after the fact.