Veeam Software has unveiled its latest Data and AI Trust Gap Report, revealing a growing disconnect between rapid AI adoption and the ability of organizations to ensure trusted, secure, and governed data. The findings, announced at VeeamON London, show that while 88% of enterprises are already using or piloting AI agents, only 7% are truly AI-ready.
The global study, based on insights from 600 senior executives across industries including financial services, healthcare, manufacturing, retail, and technology, underscores a critical issue: AI innovation is outpacing data governance and trust frameworks. In fact, 95% of organizations reported that data challenges have already slowed their AI initiatives, highlighting a major barrier to scaling AI effectively.
“Most organizations don’t have an AI adoption problem; they have an AI trust problem,” said Anand Eswaran, CEO of Veeam.
One of the most striking findings is the widening AI trust gap, where adoption is high but confidence in control remains low. Only 28% of organizations are confident they can detect AI systems operating outside approved parameters, raising concerns about operational risks and governance failures.
The report also exposes a disconnect between executive perception and operational reality. While 65% of CEOs believe they have full visibility into AI systems, only 48% of technical leaders agree. Similarly, 52% of CEOs feel they actively lead data initiatives, compared to just 41% of CISOs and 38% of CIOs, indicating fragmented accountability.
Despite these challenges, the potential upside remains significant. Nearly 48% of executives believe that trusted and compliant data could unlock over 25% revenue growth, demonstrating the strategic importance of building reliable data foundations for AI.
Veeam’s research further highlights emerging risks tied to “Shadow AI”, with 95% of organizations reporting unauthorized AI usage and 44% identifying increased cybersecurity risk as a top concern. At the same time, regulatory pressures such as the EU AI Act are pushing organizations to improve governance, with 47% citing auditability of AI decisions as a major compliance challenge.
The report concludes that success in the next phase of AI will depend on establishing trust as a core operational capability ensuring visibility, governance, security, and resilience across data ecosystems.
Organizations that achieve this alignment are already seeing results. Among fully AI-ready enterprises, 97% report measurable business value from AI, compared to just 48% overall, reinforcing the importance of closing the AI trust gap to unlock real business outcomes.
