MIND, in partnership with the CISO Executive Network, today announced new research, The Impact of Data Trust on AI Initiative Success, which examines the role of data trust in AI success. The findings point to a widening gap between rapid AI adoption and the ability to secure and govern the data that powers it.
AI is already embedded across the enterprise. According to the report, 90% of organizations are running enterprise GenAI at scale, yet 65% of CISOs lack confidence in their data security controls and only 20% of AI initiatives meet their intended KPIs.
The research introduces a clear insight: data trust is the degree of confidence that systems, including AI, use data safely and appropriately. When that trust is high, organizations move faster. When it is not, AI slows, stalls or introduces risk that outweighs its value.
The study, based on a survey of 124 CISOs and in-depth interviews with senior practitioners, highlights several consistent patterns. Organizations have policies for AI, but struggle to enforce them at machine speed. Data estates remain unclassified and ungoverned. Security frameworks were built for human behavior, not autonomous systems. The result is measurable failure, not theoretical risk.
Nearly two thirds of CISOs report low confidence in their ability to prevent unsafe AI data access. At the same time, business pressure to accelerate AI adoption continues to increase, compounding exposure.
The report frames AI as a stress test of existing security fundamentals. Organizations with strong data foundations are positioned to accelerate. Those without face a growing risk of failure, including stalled initiatives, regulatory exposure and potential business disruption.
At its core, the research reframes data security as a business enabler. As companies embrace AI innovation, high data trust moves beyond protection to become a competitive accelerant.
MIND’s perspective reflects this shift. The company positions data security not as a barrier to AI, but as the condition that makes AI viable at scale. By enabling organizations to understand, control and act on data risk in real time, MIND supports a model of Stress-Free DLP, where security operates with the speed and precision that AI demands.
The full report, “The Impact of Data Trust on AI Initiative Success,” is available now.
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New Research from MIND Reveals Critical Impact of Data Trust on AI Initiative Success
MIND, in partnership with the CISO Executive Network, today announced new research, The Impact of Data Trust on AI Initiative Success, which examines the role of data trust in AI success. The findings point to a widening gap between rapid AI adoption and the ability to secure and govern the data that powers it.
AI is already embedded across the enterprise. According to the report, 90% of organizations are running enterprise GenAI at scale, yet 65% of CISOs lack confidence in their data security controls and only 20% of AI initiatives meet their intended KPIs.
The research introduces a clear insight: data trust is the degree of confidence that systems, including AI, use data safely and appropriately. When that trust is high, organizations move faster. When it is not, AI slows, stalls or introduces risk that outweighs its value.
The study, based on a survey of 124 CISOs and in-depth interviews with senior practitioners, highlights several consistent patterns. Organizations have policies for AI, but struggle to enforce them at machine speed. Data estates remain unclassified and ungoverned. Security frameworks were built for human behavior, not autonomous systems. The result is measurable failure, not theoretical risk.
Nearly two thirds of CISOs report low confidence in their ability to prevent unsafe AI data access. At the same time, business pressure to accelerate AI adoption continues to increase, compounding exposure.
The report frames AI as a stress test of existing security fundamentals. Organizations with strong data foundations are positioned to accelerate. Those without face a growing risk of failure, including stalled initiatives, regulatory exposure and potential business disruption.
At its core, the research reframes data security as a business enabler. As companies embrace AI innovation, high data trust moves beyond protection to become a competitive accelerant.
MIND’s perspective reflects this shift. The company positions data security not as a barrier to AI, but as the condition that makes AI viable at scale. By enabling organizations to understand, control and act on data risk in real time, MIND supports a model of Stress-Free DLP, where security operates with the speed and precision that AI demands.
The full report, “The Impact of Data Trust on AI Initiative Success,” is available now.
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This entry was posted on April 8, 2026 at 9:00 am and is filed under Commentary with tags MIND. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.