Unlocking AI Success: The Metadata Advantage

By Brian Brewer | Published August 1, 2025, 09:00 AM EDT

As of 12:03 PM EDT on Friday, July 25, 2025, the AI revolution is at a crossroads. With enterprises racing to adopt artificial intelligence, a stark reality emerges: Gartner (2025) predicts 90% of AI projects will fail by 2026. Having consulted with SMBs and enterprises for over two decades, driving hands-on principal architecture and CTO-level strategies, I’ve seen this failure rate firsthand. This article uncovers the root causes—and reveals how metadata, leveraged through my experience at InfoLibrarian™, can save your AI initiatives.

The Failure Epidemic

AI’s promise is immense, but the pitfalls are deeper than most realize. Here’s why 90% stumble:

  • Data Quality Gaps: Gartner (2025) notes 60% of failures stem from poor data quality—missing context, inconsistencies, or outdated sources.
  • Lack of Semantic Understanding: AI models need more than raw data; they require metadata to interpret meaning, which static systems often lack.
  • Legacy Integration Bottlenecks: Rigid data warehouses and catalogs slow real-time data flows, choking AI’s adaptability.

I’ve witnessed this with clients—from a healthcare provider struggling with untracked data lineage to a financial firm hindered by batch-processed metadata.

The Metadata Solution

Drawing on my journey, from consulting firms to leading InfoLibrarian™’s pivot, metadata emerges as the antidote. Here’s how it turns the tide:

  • Metadata-as-Code: Automates data lineage and governance, ensuring AI models use trusted, traceable data.
  • Data Contracts: Enforces quality standards between data producers and consumers, aligning AI with business needs.
  • Context Engineering: Powers dynamic adaptability, integrating with the InfoLibrarian™ Modernization Framework to enhance AI readiness.

A healthcare client I guided improved their data infrastructure for AI readiness with metadata-driven governance, showcasing this approach’s potential.

Real-World Impact

Metadata transforms AI outcomes. For instance, a retail client streamlined data preparation with event-driven metadata, paving the way for AI adoption. My 20+ years of hands-on consulting—leading successes in Customer Success Stories—demonstrate that metadata is a critical enabler for AI readiness.

Your AI Success Blueprint

Don’t let your AI project join the 90% failure rate. Struggling with AI? Book a Strategy Call to leverage my expertise and chart a path to success.

About the Author

Brian Brewer, CTO of InfoLibrarian™, brings over 20 years of consulting experience, turning data challenges into opportunities. His Metadata Value Method™ drives the company’s modernization mission. Read Brian’s Story | Explore Articles