Real-Time Data Crucial for AI Trust
A comprehensive global study, titled The AI Trust Gap Report, conducted by Denodo has revealed significant challenges facing the adoption of agentic AI. This study surveyed 850 executives and found that a ‘trust gap’ is a major obstacle, as 66% of organisations emphasise the need for real-time data access to ensure trustworthy AI operations.
Denodo, known for its leadership in data management, highlights that fragmented data sources and inadequate governance are major barriers preventing the transition from AI insights to actionable AI. The research indicates that as AI evolves from simple chatbots to more autonomous agents capable of independent decision-making, the accuracy and governance of data become increasingly critical.
Among the key findings, 63% of organisations face difficulties in ‘finding relevant data’ within specific business contexts. This is identified as a primary obstacle to deploying AI effectively. Meanwhile, 67% of respondents report challenges in maintaining consistent security and access controls, emphasizing the need for improved data management practices.
Complexity and Performance Issues
The study reveals that the average enterprise AI initiative now utilises over 400 data sources, with 20% of organisations managing more than 1,000. As a result, nearly 60% of participants report difficulties in optimizing performance for the intensive workloads required by large-scale AI. This complexity often leads to performance bottlenecks that hinder the effective deployment of AI solutions.
Dominic Sartorio, vice president of Product Marketing at Denodo, stated, “When an AI agent triggers a business outcome, there is zero room for stale or ungoverned data. To scale agentic AI with confidence, businesses must move beyond static data silos and adopt a foundation of live, governed, and contextually relevant information.”
The report concludes that the ‘trust gap’ is not due to failures in AI models themselves but rather reflects shortcomings in the underlying data architecture. To progress from experimental AI to automated scale, organisations must bridge the divide between their disparate data estates and the real-time requirements of agentic systems.
Denodo’s report emphasises the urgency of addressing these challenges to ensure that AI can move forward effectively. Organisations must prioritise the integration of live and governed data, which is crucial for the success of agentic AI and its ability to deliver reliable business outcomes.
As AI technologies continue to advance, the need for robust data governance and real-time data access becomes ever more pressing. Denodo’s platform enables businesses to achieve up to 4x faster time-to-insight and 345% return on investment, demonstrating the significant efficiency gains possible with streamlined data management.
