<img alt="" src="https://secure.leadforensics.com/106433.png" style="display:none;">
Landing Banner Skinny (4)-1

2026 Gartner prediction - 60% of AI use cases will fail due to a lack of AI data-ready practice.*

Data Fidelity: a key ingredient for AI when referencing data history

Results you can trust depend on your AI agents having access to authentic data in its fullest context, which is not possible if you alter the data structure through archiving

Gartner researchers predicted in 2026 that "organizations that don’t enable and support their AI use cases through an AI-ready data practice will see over 60% of AI projects fail to deliver on business SLAs and be abandoned."*

Authentic data lets your AI agents deliver accurate results.

DataNovata enables you to retain the full data fidelity for your data history for your AI learning models to minimize data gaps and maximize your level of trust.

Get in touch with our data experts to learn more.

*"A Journey Guide to Deliver AI Success Through AI-Ready Data", 11 July 2025, Ehtisham Zaidi, Roxane Edjlali

The proposition: anything less than 100% data fidelity is not AI-ready

Your live data has 100% fidelity. However, when you use a third-party archive platform, your vendor may not alter the data, but they will often adjust the database schema, table relationships, and metadata to suit their archive software and storage design. Even if the data is intact, the authentic historical fabric is lost.

This means AI will learn the “what” of your data, but not the “how”, leaving you to put the missing pieces together.

Read the full article to learn more.

©2026 DataNovation Ltd - All rights reserved. Privacy Policy

Gartner is a registered trademark of Gartner, Inc. and its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates. All rights reserved.