NetApp, the intelligent data infrastructure company, has released its 2025 Enterprise AI Maturity Study, conducted by IDC, revealing that organizations leading in artificial intelligence—termed “AI Masters”—are distinguished not by experimentation, but by their ability to manage and protect data effectively. The report shows that these advanced enterprises achieve 24.1% higher revenue growth and 25.4% better cost efficiency than less mature peers, emphasizing that data readiness, protection, and infrastructure modernization now define AI success.
“AI is no longer about proof of concept—it’s about proof of value,” said Syam Nair, Chief Product Officer at NetApp. “The research proves that the true differentiators are data quality, protection, and scalable architecture. Companies investing in intelligent data infrastructure are the ones translating AI into measurable business outcomes.”
Data and infrastructure: the real differentiators
The IDC study highlights that while enthusiasm for AI remains high, infrastructure readiness continues to be a bottleneck. Although the number of enterprises requiring a total storage overhaul dropped from 63% in 2024 to 37% in 2025, a striking 84% still report their storage systems are not fully optimized for AI workloads.
AI Masters—organizations that have aligned data governance, storage, and security architectures—are significantly outperforming their competitors. They treat data not as a byproduct but as a strategic asset, ensuring accessibility, scalability, and resilience across hybrid and multi-cloud environments.
AI security takes center stage
As the adoption of agentic AI (self-improving, autonomous systems) accelerates, security has become an enterprise-wide priority. According to the study, 62% of AI Masters increased their AI security budgets in the past year, compared to just 16% among less mature companies. This indicates a decisive shift toward secure-by-design AI operations, where infrastructure resilience and data protection underpin every stage of AI development.
NetApp’s research also shows that companies with robust data classification and monitoring frameworks are better equipped to handle new regulatory requirements and mitigate risks associated with synthetic data and model bias.
From experimentation to enterprise-scale AI
The findings suggest that the AI maturity curve has steepened: while early adopters focused on pilots, industry leaders are now standardizing enterprise-scale AI pipelines integrated with modern data architectures. The report underscores the importance of cloud-smart, adaptive infrastructure that can scale AI workloads efficiently without compromising compliance or performance.
For CIOs and CTOs, the message is clear: the next wave of AI advantage will come from operational readiness, not just innovation. Intelligent data infrastructure—capable of managing both structured and unstructured data—has become the core enabler of long-term competitiveness.
IDC’s bottom line
IDC’s 2025 study concludes that scaling AI responsibly requires a trusted, modern, and intelligent data foundation. Enterprises that align their data lifecycle, security posture, and infrastructure design are not only leading the current AI wave but are also preparing for the emergence of autonomous, self-optimizing AI systems.
NetApp’s report reinforces that as AI transitions from hype to hard value, data readiness and infrastructure agility will define enterprise success in the AI economy.
