More than half of organisations say finding trustworthy and relevant data remains a significant barrier to AI deployment
Businesses are under growing pressure to move beyond AI experimentation and deploy autonomous AI agents capable of making decisions and taking action. Yet new global research from Denodo suggests many organisations have not solved the fundamental data challenges required to make that vision a reality.
The study, conducted by Arlington Research among 850 executives and business decision-makers worldwide, found that 56% of organisations say finding trustworthy and relevant data remains a significant barrier to AI deployment. At the same time, 66% believe AI systems must have access to near real-time information if they are to be trusted.
The findings point to a growing gap between AI ambition and AI readiness, as organisations look to adopt agentic AI systems that can move beyond generating insights to executing tasks and business processes autonomously.
According to Denodo, this reflects a broader shift in enterprise AI. As organisations move towards autonomous AI, success will depend not only on giving AI access to enterprise data but also on providing the trusted business context needed to interpret that data and use it correctly and appropriately.
Additional findings from the research include:
- 67% of organisations struggle with AI data security and access controls
- 43% of organisations draw on more than 400 data sources to support AI initiatives
- 60% report difficulties optimising performance for the intensive workloads required by large-scale AI deployments
Together, the findings suggest that the biggest barrier to agentic AI adoption may not be the technology itself, but the quality, accessibility and governance of the data that underpins it.
“The research shows organisations recognise the importance of trusted, real-time data, but the next challenge goes beyond access,” said Dominic Sartorio, Vice President of Product Marketing at Denodo. “AI agents don’t simply need access to enterprise data. They need trusted business context that tells them what the data means, whether it can be trusted and how it should be used. Without that foundation, organisations will struggle to deploy AI that people can rely on.”
The research also highlights the complexity facing many enterprises as they seek to operationalise AI. More than four in ten (43%) organisations now rely on over 400 separate data sources for AI initiatives, creating significant challenges around governance, security, performance and consistency.
According to Denodo, organisations that want to move from AI experimentation to enterprise-scale deployment must focus on creating a trusted data foundation that provides governed, secure, and real-time access to information across the business.
“The conversation around AI has largely focused on models and applications,” added Sartorio. “What this research shows is that data readiness has become the defining factor. Organisations that solve the trust challenge will be far better positioned to unlock the full potential of agentic AI.”
The full report explores the challenges organisations face as they prepare for the next phase of AI adoption and examines the data management strategies required to support autonomous AI systems.
Download the Full Report
Explore the complete findings of the AI Trust Gap Report conducted by Arlington Research.
