Legacy Data Infrastructure Is Driving $108 Billion in Annual Wasted AI Investment, New Survey Finds
New
complexity is rising rapidly or too quickly to manage, driven by growth in data, platforms and AI,
straining governance and security
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The report surveyed over 1,200 C-level executives and IT leaders across 15 countries, including 307 respondents in the
As data environments grow more complex, organizations are finding it harder to maintain visibility, control and accountability across their systems. With leaders expecting investment in AI to grow by 76% over the next two years, those challenges are intensifying, placing greater strain on security and data governance. Among
- Only 43% report having predictive or automated infrastructure operations, limiting their ability to manage complexity;
- 57% say the complexity of their data makes identifying a data breach more difficult;
- 59% fear a critical data loss would be catastrophic; and
- Half (50%) say their systems are complex enough that executives would lose sleep if they understood the risks.
"AI is raising the bar for how organizations govern and manage their data," said
The Great AI Divide
AI adoption is nearly universal, with 98% of organizations using, piloting or exploring AI, but readiness to scale and realize value varies widely. The findings reveal a clear divide between organizations that have built strong data management foundations and those struggling to keep pace as AI adoption accelerates. The difference is not whether companies are using AI or how large a company is, but whether they pair a clear AI vision and leadership alignment with data environments that are structured, governed and built to scale.
In the
That gap is reflected directly in AI performance and return on investment (ROI):
- 84% of data-mature organizations report measurable AI ROI, compared with only 48% of data laggards.
- Data quality is the most commonly cited driver of AI success, with 59% of organizations attributing successful AI projects to the use of high-quality data – rising to 75% among data-mature organizations, compared to 47% for those with weaker data practices.
- Among organizations with mature data practices, 59% say AI is critical to their business, compared with just 18% of organizations with weaker data foundations.
Data-Mature Organizations Show Clear Differences in Data Infrastructure Readiness
Organizations with strong data foundations demonstrate shared practices that set them apart, particularly when it comes to leadership alignment, infrastructure modernization and operational discipline. Among organizations leading in data maturity in the
Companies with mature data practices are also significantly ahead in automation, with 65% reporting automated infrastructure, compared with just 27% of organizations with weaker data practices, reducing operational friction as AI scales. Additionally, 82% of data-mature companies report having sustainable design and built-in resilience, reflecting an infrastructure approach designed to support long-term growth, efficiency and risk reduction as AI adoption expands, compared with just 19% among organizations with weaker data practices.
The research further underscores the importance of leadership engagement. While 96% of these organizations say they need outside help with data infrastructure, many continue to struggle to translate that need into coordinated action, highlighting a gap between recognizing the challenge and executing a long-term data strategy.
"As AI becomes central to how every business operates, leadership has to treat data foundations as a strategic requirement, not just a technical concern," said
For more information on how
Additional Resources
- Report:
Hitachi Vantara State of Data Infrastructure Report - Blog: Operationalizing Agentic AI with
Hitachi iQ Studio and NVIDIA Nemotron 3 - Press Release:
Hitachi Vantara Launches Virtual Storage Platform One Block High End Storage to Power the Next Era of AI and Mission-Critical Workloads - Blog: From Science Fiction to Factory Floor: The Physical AI Revolution Takes Shape
- Webinar: Build Modern AI-Ready Infrastructure Without Starting Over
- Blog: The End of Data Infrastructure as We Know It. And That's a Good Thing.
- Press Release:
U.S. Data Concerns Soar as AI Surges – 37% of IT Leaders Identify Data Quality asMajor Barrier to AI Success
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