Gartner® ReportHow to Evaluate AI Data Readiness
Complimentary access until September 2025
“This research proposes an evaluation method to verify AI-readiness of data for each specific use case, establishing what prior context from existing uses of data may be applicable and proposing mitigation strategies where needed.”
Why you should read this Gartner® Report:
AI is only as strong as the data that fuels it.
As organizations scale artificial intelligence initiatives, data and analytics leaders must ensure data is not only available but AI-ready — aligned, contextual, representative, and trusted. In this Gartner® report, How to Evaluate AI Data Readiness, you’ll learn how to assess data across readiness modes — from proof of concept to production — and mitigate the risks of bias, hallucination, and drift that can undermine model performance.
CIOs, CDOs, and Heads of Data Management are under increasing pressure to operationalize AI responsibly. This report delivers critical insights to help you:
- Evaluate whether your data is ready for AI — and why traditional quality standards fall short
- Understand and apply Gartner’s AI Data Readiness Checklist and Priority Matrix
- Mitigate the risk of poor data quality, governance gaps, and overconfident AI teams
- Shift risk management from manual expert review to automated metadata-driven validation
With over 50,000 data management inquiries analyzed, we believe this report from Gartner® reflects the extensive field knowledge of what it takes to succeed in AI deployment — from metadata usage to real-time monitoring.
Who should read this?
- Chief Data Officers (CDOs) and CIOs guiding enterprise AI adoption
- Data and Analytics Leaders managing governance, quality, and architecture
- Data Scientists and Engineers seeking clarity on what constitutes AI-ready data
- AI Program Leads responsible for risk management, productionization, and model trust
- If you’re involved in designing, governing, or scaling AI initiatives, this report is a must-read.
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.
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Date of publication: 31 January 2025
Authors: Mark Beyer, Ehtisham Zaidi, Roxane Edjlali
Disclaimer
Gartner, Cool Vendors in AI Core Technologies, Farhan Choudhary, Erick Brethenoux, Svetlana Sicular, Chirag Dekate, Soyeb Barot, Sumit Agarwal, Julian Sun, 11 May 2021.
GARTNER and Cool Vendor Badge are registered trademarks and service marks of Gartner and Hype Cycle is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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