Follow These 5 Steps for AI-Ready Data

AI runs on data, but it’s not just any data that drives real results. For AI to deliver the kind of business value organizations expect, the data behind it needs to be high quality: contextual, governed, and aligned to specific use cases.

When over half of AI projects never make it into production, how can you set yourself up for success? This Gartner report outlines five practical steps for preparing enterprise data for AI and GenAI initiatives. Download it to see:

• Why data quality isn’t the same thing as AI readiness

• What “AI-ready data” really means—and requires

• Detailed instructions for each of the five data preparation steps

• You’ll also find information about foundational steps in assessing data, the types of data sources to include, and the challenges of using each.

You’ll also find information about foundational steps in assessing data, the types of data sources to include, and the challenges of using each.

_{Follow These Five Steps to Make Sure Your Data Is AI-Ready, 2024, Melody Chien, Ehtisham Zaidi, Mark Beyer, 18 October 2024}

_{GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved.}