Cloudera has released its latest global survey, The Great AI Re-Architecture, revealing a fundamental shift in enterprise IT as organizations redesign their data architectures to meet the demands of AI. Based on responses from 1,500 Enterprise Architects, Cloud Infrastructure Leads, and Data Architects worldwide, the report finds that while AI adoption has become mainstream, legacy data architectures are increasingly limiting organizations' ability to scale AI securely, efficiently, and cost-effectively.
95% of enterprises delayed or canceled AI initiatives due to governance and compliance challenges.
77% of organizations are actively using AI, but 72% require significant architecture overhaul.
75% say AI integrations have changed data storage and architecture practices.
84% report increased infrastructure costs driven by AI workloads.
73% say AI has made data governance more complex.
66% moved AI workloads from public cloud back to private cloud or on-premises.
The findings point to a fundamental shift in enterprise IT architecture. While 77% of organizations are actively using AI, nearly all (95%) have delayed or canceled AI initiatives over the past year because of data governance, compliance, or regulatory challenges. To overcome these challenges, 72% say their current data architecture requires a significant overhaul to meet future AI requirements, suggesting today's infrastructure was not built for the demands of modern AI. Together, these findings highlight what Cloudera calls "The Great AI Re-Architecture"—the mass transition from legacy data architectures toward hybrid environments that enable organizations to bring trusted AI to trusted data, wherever it resides.
Three-quarters (75%) of respondents say AI integrations have changed their organization's data storage and architecture practices, while 84% report increased infrastructure costs driven by AI workloads. Nearly three-quarters (73%) of respondents say AI has made data governance more complex, and more than half (55%) report delaying or canceling more than six AI projects over the past 12 months due to governance, compliance, or regulatory challenges. Almost every respondent (97%) reports moving data between environments at least monthly, making consistent governance across cloud, private cloud, on-premises, and edge environments essential for scaling AI securely.
Two-thirds (66%) of respondents say they have moved AI workloads from public cloud environments back to private cloud or on-premises infrastructure during the past year, signaling a broader shift toward hybrid architectures. One-quarter (25%) say they plan to prioritize a hybrid-first architecture over the next two years, reinforcing that the future of enterprise AI will be defined by flexibility rather than a single infrastructure strategy.
"This current era of AI is forcing organizations to rethink the foundations of their technology infrastructure," said Sergio Gago, Chief Technology Officer at Cloudera. "Many enterprises are discovering that the architectures built for traditional analytics weren't designed for the scale, governance, and flexibility AI demands today. Success will depend on building a data foundation that gives organizations the freedom to run AI wherever it makes the most sense, without compromising control or security."
About Cloudera
Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, sovereign clouds, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights.
