Ataccama Data Trust Assessment reveals data quality gaps blocking AI and compliance
Organizations average 42/100 on data trust maturity, with the lowest scores in remediation and quality, as AI and regulatory demands expose weaknesses that slower-moving environments once masked
Boston, Mass. – August 27, 2025 – Ataccama, the data trust company, shared early findings from its Data Trust Assessment, a benchmark of the trustworthiness of enterprise data and how ready organizations are to support AI and compliance. Since its launch in March, the assessment has been completed over 150 times by CDOs, business leaders, and data management professionals.
Key findings show organizations averaging just 42/100 on data trust maturity, with the lowest scores in areas such as remediation workflows, policy enforcement, and reference/master data quality. These gaps reveal the pressure AI adoption and tightening regulations are putting on fragile data foundations. What could once be hidden in slower-moving environments is now exposed, with AI and compliance initiatives failing when data can’t be trusted.
The assessment is designed to move organizations from ad hoc data management projects to a measurable, maturity-based program across people, process, and technology. It provides a baseline score, peer benchmarks, and a ranked set of priorities across four pillars – quality, governance, observability, and improvement (remediation and workflows) – along with clear next steps. By re-running the assessment, leaders can track the progression of their data program maturity and scale deliberately rather than reactively.
AI continues to underdeliver not because of models, but because of data. Ataccama’s broader research shows that a third of organizations report meaningful AI progress, while most cite data quality as the top blocker. Leaders spend more time finding, validating, and reconciling data than deploying models. Data quality is the engine of data trust, and trust is the foundation for AI and compliance.
Sector patterns vary, but the root cause is consistent: without trusted data, outcomes suffer. In financial services, weak observability and lineage make it difficult to audit flows and trace reports back to source, raising regulatory risk. In manufacturing, inconsistent product data slows reporting, disrupts supply chains, and inflates compliance costs. Regardless of industry, data quality is the prerequisite for trusted outcomes.
“Quantitative intuition, the mix of data and judgment, drives better decisions. Untrusted data erodes every decision it touches,” said Jay Limburn, Chief Product Officer at Ataccama. “Too many organizations invest in data programs without a clear view of how trustworthy their data landscape really is. We built the Ataccama Data Trust Assessment to surface where trust breaks down and to guide what to fix first. Data trust creates value on every front. Without real insight into data quality, businesses risk cascading failures – from unreliable AI outputs to stalled growth. Trust has to permeate every layer, from data and models to decisions.”
Take the Data Trust Assessment today and download the Data Trust Playbook to operationalize data quality and trust at scale.
About Ataccama
Ataccama is the data trust company. Organizations worldwide rely on Ataccama ONE, the unified data trust platform, to ensure data is accurate, accessible, and actionable. At the core of the platform is our leading data quality suite that integrates data quality rules, catalog, lineage, observability, and governance to continuously improve the reliability of enterprise data. This quality-first foundation makes data quality the engine of trust, powering AI, analytics, and operations with confidence. Ataccama helps organizations drive innovation, reduce costs, and mitigate risk. Recognized as a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality and the 2025 Magic Quadrant for Data and Analytics Governance, Ataccama continues to set the standard for enterprise-grade data trust. Learn more at www.ataccama.com.
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