Mind the Gap! Where Traditional Data & Analytics Governance Fails AI

In his article, David did an excellent job summarizing and critiquing the 2025 Gartner® Magic Quadrant™ for Data and Analytics Governance Platforms, written by Gartner Analysts Guido De Simoni, Anurag Raj, Melody Chien, and Stephen Kennedy and published on 7 January 2025 – ID G00807073.

Gartner reports, notably their Magic Quadrants™, are reliable technology insights and guidance sources. While expansive in scope, they cannot always capture every requirement, vendor offering, and new capability.

What is the AI Governance Gap?

As David points out, while doing a great job covering traditional data and analytics governance, this report has largely missed or under-evaluated  AI/ML governance requirements such as:

• Bias detection and mitigation: Identifying and reducing biases in training data and models.
• Explainability of models: Making model predictions understandable to humans.
• Model versioning and dependency management: Tracking model versions and their associated data and code.
• Privacy-preserving ML techniques: Protecting sensitive information used in model training.
• Monitoring for model drift and fairness: Tracking changes in model performance and fairness over time.
• Data Science reproducibility: Ensuring that data science experiments and results can be reliably reproduced.

What the AI Governance Gap Means to You

To help you understand the AI governance gap in general and what it means to your organization in particular, we have brought together three subject matter experts for the March 21, 2025, at 9:00 AM ET for this month’s Insight Jam Session: Mind the Gap! Where Traditional Data & Analytics Governance Fails AI.

https://insightjam.com/posts/81597236?utm_source=manual

These experts include David Sweenor of TinyTechGuides, Dr. Irina Steenbeek from Data Crossroads, and DataOps.live executive Thomas Steinborn.

In this session, they will address these critical AI governance questions such as:

• What’s unique or different about governing AI?
• Where does AI require additional governance capabilities beyond traditional data and analytics governance?
• What are the benefits of AI governance?  What are the risks?
• How can organizations best fill their AI governance gap?
• Where is the best place to start?

Think of this session as a free Oyster card on your journey to AI governance success.

See you then and there.

For More Information

If you want to download the Gartner report.

• https://www.informatica.com/lp/gartner-leadership.html
• https://www.collibra.com/resources/2025-gartner-magic-quadrant-for-data-and-analytics-governance-platforms
• https://atlan.com/gartner-magic-quadrant-data-governance-2025

You can read David’s article here.

https://tinytechguides.com/blog/the-gorilla-in-the-quadrant-why-your-data-and-ai-governance-strategy-needs-more-than-gartners-report/