Commissioned by AvePoint
Published October 2025
Executive summary
AI is no longer a future disruptor – it’s a present reality. But as adoption accelerates, trust in AI outputs is eroding. Organizations realize that without strong governance, resilient data strategies, and a commitment to quality, AI can just as easily become a liability as a competitive advantage.
Building on AvePoint’s 2024 report, the 2025 report tracks the evolution from AI experimentation to enterprise-wide enablement. The findings revealed that despite widespread AI adoption efforts, critical operational gaps persist around data security and quality, with these foundational issues delaying AI rollouts by up to a year for three-quarters of organizations.
Key takeaways:
- AI rollouts stall before takeoff. 86% of organizations delayed AI deployments by up to a year due to security and data quality concerns.
- AI security incidents are too common. 75% experienced at least one AI-related breach in the past year, primarily due to oversharing sensitive employee or customer data.
- AI data frameworks exist – but fail to deliver. While 90% of organizations claim to have an information management framework, only 30% say it classifies and protects data effectively.
- AI training alone won’t fix trust. 99.5% have invested in AI literacy, but inaccurate outputs and hallucinations still erode employee judgment and decision-making.
- AI customer impact falls short. Organizations say enhancing customer insights and personalization is their top AI goal – yet there is a 5.8% gap between what they hope to achieve and what they actually do.