Research Finds Data Readiness and Infrastructure as Critical to Success in the AI Era
MWN-AI** Summary
NetApp® (NASDAQ: NTAP) unveiled key findings from its global Enterprise AI maturity study conducted by IDC, highlighting the critical role of data readiness and infrastructure in leveraging artificial intelligence (AI) for business success. The 2025 study marks a notable shift, emphasizing that organizations must transcend proof of concept to showcase the proof of value through effective AI implementations.
The study reveals that large enterprises are leading the way, as AI Masters—those investing in advanced infrastructure, governance, and security—outperform their counterparts significantly. For instance, AI Masters reported a 24.1% revenue increase and a 25.4% reduction in costs compared to less mature organizations. Despite improvements, a significant 84% of firms still face suboptimal storage for AI, pointing to infrastructure as a critical bottleneck.
Security is also a growing concern. The findings demonstrate that 62% of AI Masters increased their security budgets for AI initiatives over the past year, contrasting with only 16% of less mature firms doing so. Organizations are learning that effective AI goes beyond simple adoption; it requires deep integration of data governance, security, and infrastructure capabilities.
The evolving landscape reveals that merely experimenting with AI is insufficient. Enterprises need to cultivate a robust, intelligent data infrastructure that supports scalable, adaptable, and secure architectures. This foundation is vital for turning AI pilots into impactful, production-grade applications that deliver measurable business results.
In conclusion, the study underscores that the journey to successful AI implementation is heavily anchored in data quality and infrastructure readiness, highlighting that organizations must adapt their strategies to meet the demands of an AI-driven future. For further details, the complete report is accessible via NetApp.
MWN-AI** Analysis
The findings from NetApp’s latest global Enterprise AI maturity study underscore the critical importance of data readiness and infrastructure in harnessing AI's full potential. With large enterprises taking the lead in building AI-ready infrastructures, smaller firms must prioritize similarly robust data practices to remain competitive.
The research indicates a marked difference in performance between AI Masters—organizations with advanced AI infrastructures—and their less mature counterparts. With a 24.1% revenue improvement and 25.4% cost savings attributed to these leaders, it's clear that investing in comprehensive data governance and modern, scalable technologies pays off.
However, challenges persist. A significant 84% of organizations still find their storage not fully optimized for AI, revealing that much work remains in streamlining operations. This situation paints a picture of urgency: organizations that neglect their data infrastructure might struggle to translate AI experimentation into sustainable business results.
Security is also a major focus. As AI initiatives grow, so do the complexities surrounding data protection, with 62% of AI Masters increasing their security budgets—a stark contrast to only 16% of less mature firms. This highlights that to scale AI technologies responsibly and effectively, organizations must embed strong security frameworks from the onset.
In such a rapidly evolving landscape, companies should not only aim to upgrade piecemeal but think strategically about their architectures. Transitioning to cloud-smart, adaptive systems is essential. Thus, the advice for market participants is clear: prioritize investments in intelligent data infrastructures that emphasize data quality, security, and scalability to realize measurable AI-driven business outcomes. Furthermore, enterprises sticking to outdated systems risk falling behind in the competitive race for AI excellence.
**MWN-AI Summary and Analysis is based on asking OpenAI to summarize and analyze this news release.
Study finds industry and size matter: large enterprises outpace peers in building AI-ready infrastructure
NetApp® (NASDAQ: NTAP), the intelligent data infrastructure company, today unveiled a new global Enterprise AI maturity study conducted by IDC*. This second annual study reveals a sharp shift in how enterprises approach artificial intelligence and confirms AI has entered a new phase where the most mature organizations prioritize data readiness, protection and security while they make impactful infrastructure decisions and investments to support current and next-gen AI.
Findings from 2024 highlighted AI’s potential to drive dramatic business outcomes, but also exposed deep gaps in infrastructure, governance, and skills. In 2025, the conversation has evolved: organizations are now confronting ROI pressures, fragmented adoption, and the need to embed data governance and security from the start.
“AI is no longer about proof of concept—it’s about proof of value,” said Syam Nair, Chief Product Officer at NetApp. “IDC’s latest research shows that the real differentiators are data preparedness and infrastructure: the companies focusing on data quality and building modern, cloud-smart, scalable, and adaptive architectures are the ones turning AI into true business impact. That’s why NetApp believes every organization needs an Intelligent Data Infrastructure to succeed in the AI era.”
Key findings from the 2025 study include:
- Maturity pays off. AI Masters (organizations pursuing the most advanced AI infrastructure, data governance and security approaches) consistently outperform their less mature peers across every AI business outcome: Masters achieved 24.1% revenue improvement and 25.4% improvement in cost savings, far outpacing less mature peers.
- Infrastructure remains a bottleneck. While the percentage of firms reporting that their storage required a major overhaul dropped from 63% in 2024 to 37% in 2025, 84% still say their storage is not fully optimized for AI.
- Security is now front and center. 62% of AI Masters increased security budgets for AI initiatives in the past year, compared to just 16% of less mature organizations.
- Agentic AI favors the Masters. With stronger data, security, and infrastructure foundations, AI Masters are already ahead. Less mature peers remain siloed in GenAI adoption, an approach that will not scale to Agentic AI’s enterprise-wide demands.
Together, these findings highlight a single point: scaling AI responsibly requires more than experimentation – it demands a trusted, modern, and intelligent data infrastructure.
“Enterprises that modernize their data pipelines, governance frameworks, security approaches, and storage architectures are the ones turning AI pilots into production-grade applications that deliver the highest measurable business outcomes,” said Dave Pearson, IDC Research Vice President, Infrastructure Solutions.
The combined 2024 and 2025 findings underscore that the difference between AI hype and AI impact lies in the data practices and architecture beneath AI initiatives. While less mature organizations may report KPI improvement, IDC finds that the greatest and most sustainable business impact comes from a focus on foundational data quality and infrastructure investments. Masters are moving beyond piecemeal upgrades toward architectures that are cloud-smart, scalable, data-aware, adaptive, and automated. In the AI era, speed, scale, security, and adaptability aren’t optional - they are key ingredients to realizing the most business value from your AI initiatives.
Methodology
In January of 2024 and June of 2025, IDC conducted a survey of +1,200 global decision makers involved in enterprise IT operations, data science, data engineering and software development related to AI initiatives. These interviews revealed in-depth information about the evolving state of AI initiatives including the array of challenges, numerous business benefits, and best practices that leading organizations have taken to achieve success.
In conducting this analysis IDC has developed an AI maturity model where organizations fall into one of four maturity levels based on their current approach to AI in terms of data and storage infrastructure, data policy and governance, resource efficiency focus, and stakeholder enablement and collaboration. These maturity levels are AI Emergents, AI Pioneers, AI Leaders, and AI Masters.
To access the full report, visit: https://www.netapp.com/media/142474-idc-2025-ai-maturity-findings.pdf
*Source: IDC InfoBrief, "Scaling Enterprise AI Responsibly: The Critical Role of Data Readiness and an Intelligent Data Infrastructure", sponsored by NetApp, doc #US53841625, October 2025
About NetApp
NetApp is the intelligent data infrastructure company, combining unified data storage, integrated data, and workload services to turn a world of disruption into opportunity for every customer. NetApp creates silo-free infrastructure, harnessing observability and AI to enable the industry’s best data management. As the only enterprise-grade storage service natively embedded in the world’s biggest clouds, our data storage delivers seamless flexibility. In addition, our data services create a data advantage through superior cyber resilience, governance, and application agility. Our workload services provide continuous optimization of performance and efficiency through observability and AI. No matter the data type, workload, or environment, with NetApp you can transform your data infrastructure to realize your business possibilities. Learn more at www.netapp.com or follow us on X , LinkedIn , Facebook , and Instagram .
NETAPP, the NETAPP logo, and the marks listed at www.netapp.com/TM are trademarks of NetApp, Inc. Other company and product names may be trademarks of their respective owners.
View source version on businesswire.com: https://www.businesswire.com/news/home/20251007931440/en/
Media Contact
Kenya Hayes
NetApp
kenya.hayes@netapp.com
Investor Contact
Kris Newton
NetApp
kris.newton@netapp.com
FAQ**
How does NetApp Inc. NTAP plan to support organizations in enhancing their AI maturity levels through improved data infrastructure and governance?
What specific strategies is NetApp Inc. NTAP implementing to address the infrastructure bottlenecks highlighted in the 20AI maturity study?
In what ways can investors capitalize on the revenue improvements indicated for AI Masters, as reported by NetApp Inc. NTAP's recent enterprise AI maturity study?
How is NetApp Inc. NTAP positioning itself to assist companies in increasing their AI security budgets, as noted in the study, to ensure responsible AI scaling?
**MWN-AI FAQ is based on asking OpenAI questions about NetApp Inc. (NASDAQ: NTAP).
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