The BARC study on AI readiness highlights what we at infoVia have long observed: AI initiatives do not fail at the model stage—they fail at the data stage.
In fact, AI readiness is often mistakenly framed as a question of compute power, modeling tools, or hiring more data scientists. But if your data is siloed, inconsistent, poorly documented, or lacking lineage, no model—no matter how sophisticated—can deliver meaningful results. The study confirms that organizations continue to wrestle with issues around data quality, integration, governance, and accessibility, resulting in AI that is technically impressive but operationally irrelevant.
You Can’t Operationalize What You Can’t Trust
AI promises speed, insight, and prediction—but only if it is trained on data that is accurate, contextual, and complete. Unfortunately, too many organizations are still treating data preparation as an afterthought, not a foundation.
At infoVia, we approach this differently. Our clients do not come to us simply to “stand up AI.” They come to us to strategically align their data with business value—which, when done right, enables the responsible, secure deployment of AI across the enterprise.
This is where our Data Liberation Methodology proves its worth. Rather than retrofitting AI on top of broken systems, we help organizations:
- Assess and cleanse their source data for consistency and quality
- Consolidate silos through governed integration
- Establish lineage and metadata visibility across the lifecycle
- Design for agility with scalable architectures like Data Vault 2.0
- Secure access at scale using infoSecur, our metadata-driven access control platform
We execute iteratively to constantly deliver value to your point of most impact, resulting in AI built on a foundation of trustworthy, auditable, and accessible data—ready to drive real decisions, not just generate flashy dashboards.
What’s Often Missed: Organizational and Structural Debt
The BARC study rightly points out that data quality is often the symptom, not the root cause. The deeper challenge is structural debt—fragmented ownership, legacy architecture, and disconnected systems that were not designed with AI in mind.
We have helped organizations in higher education, government, and industry confront this reality. By putting governance, modeling, and metadata at the core of every engagement, we do not just “clean up the data.” We reshape how organizations think about data: not as a byproduct of operations, but as a core business asset that must be shared widely—but protected fiercely.
The Path Forward: Data Strategy First, AI Second
There is a growing consensus—evident in the BARC study—that AI without data readiness is not only ineffective, but also risky. Organizations must reframe AI readiness not as a question of tools, but of strategy, structure, and stewardship.
At infoVia, we help our clients begin with business outcomes and reverse-engineer the data architecture to support them. We use metadata-driven automation to accelerate delivery and ensure consistency. We embed access control and compliance from the start—not as bolt-ons.
We have seen firsthand how this disciplined, model-driven, and security-aware approach empowers organizations to move faster with less risk—and to turn their data into a durable, competitive advantage.
Join us in transforming your data into a strategic asset. Contact infoVia today at contact@infovia.com to align your data with business value and ensure the responsible deployment of AI across your enterprise.
About infoVia
infoVia (www.infovia.com) is a strategic data consultancy dedicated to unlocking business value through trusted data ecosystems. With deep expertise in Data Vault, metadata automation, and data access control via our infoSecur platform (www.info-secur.com), we guide organizations from fractured data landscapes to scalable, secure, and AI-ready foundations.
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