A groundbreaking report has highlighted that poor data quality remains the most significant hurdle to achieving AI success, with 68 per cent of Chief Data Officers (CDOs) citing it as their top concern. The Ataccama Data Trust Report 2025, based on a survey of 300 senior data leaders, reveals that only a third of organisations report meaningful progress in AI adoption, underlining systemic challenges in data management and governance.
The findings come at a critical moment for the UK, as it accelerates its AI ambitions under the newly unveiled AI Opportunities Action Plan. The report identifies data trust as a cornerstone of successful AI deployment, warning that without reliable, high-quality data, even the most advanced AI systems risk underperformance, inefficiency, and compliance failures.
Fragmented Systems and Legacy Infrastructure
The report reveals a stark reality: 41 per cent of organisations struggle with consistent data quality, a problem exacerbated by fragmented systems and legacy infrastructure. These challenges hinder real-time data processing and complicate AI scalability, leaving many enterprises unable to leverage their data assets effectively.
The report emphasises the importance of moving beyond siloed governance structures. Consolidating data ecosystems into unified platforms enables continuous quality monitoring and real-time insights, which are critical for AI-driven transformation. Addressing these foundational gaps is essential to unlocking AI’s potential and achieving a return on investment.
As the UK seeks to position itself as a global leader in AI innovation, the report calls for national data governance standards to operationalise principles of safety, transparency, and fairness. A proposed National Data Library could serve as a benchmark, providing clear compliance guidelines and enabling organisations to create AI-ready data ecosystems.
“Enterprise AI initiatives rely on a foundation of trusted data,” Jay Limburn, Chief Product Officer at Ataccama, notes. “Without addressing systemic data quality challenges, organisations risk stalling progress. The UK’s approach to AI regulation shows how aligning data trust principles with national standards and infrastructure modernisation can deliver tangible results.”
Building Data Trust for Sustainable AI Growth
The report outlines actionable steps to build data trust, focusing on embedding governance into workflows and adopting continuous validation practices. High-quality data, it argues, accelerates decision-making, enhances customer experiences, and creates competitive advantages.
Moreover, aligning data governance initiatives with ethical AI goals ensures compliance and mitigates risks associated with data inaccuracies. By investing in modern infrastructure capable of handling real-time, high-volume data, organisations can scale AI initiatives effectively and sustainably.
As AI continues to reshape industries, the Ataccama report provides a clear roadmap for businesses to address their data challenges. Prioritising data trust not only supports compliance but also drives innovation and competitive differentiation.
The UK’s investment in supercomputing and AI growth zones represents a significant step forward, but its success depends on integrating robust data quality standards. With a comprehensive approach to data trust, the nation can solidify its position as a global AI leader, ensuring that its policies deliver measurable outcomes and long-term benefits.
