As enterprises scale artificial intelligence across their operations, limitations in legacy data architectures are prompting organisations to rethink how their infrastructure is designed and managed, according to a new global survey by Cloudera.
The report, titled The Great AI Re-Architecture, surveyed 1,500 enterprise architects, cloud infrastructure leads and data architects globally. It found that while AI adoption has become mainstream, existing data architectures are increasingly creating challenges around scalability, governance, security and cost.
According to the study, 77% of organisations are actively using AI, while 95% have delayed or cancelled AI initiatives in the past year because of data governance, compliance or regulatory challenges. At the same time, 72% said their current data architecture requires a significant overhaul to meet future AI requirements.
“This current era of AI is forcing organisations to rethink the foundations of their technology infrastructure,” said Sergio Gago, Chief Technology Officer, 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 organisations the freedom to run AI wherever it makes the most sense, without compromising control or security.”
AI drives infrastructure resets
The expansion of AI across enterprise operations is also putting pressure on existing storage and infrastructure environments. 75% of respondents said AI integrations have changed their organisation’s data storage and architecture practices, while 84% reported increased infrastructure costs as a result of AI workloads.
Mayank Baid, Regional Vice President, India & South Asia, Cloudera, said Indian enterprises are increasingly moving from AI experimentation towards converting AI investments into business outcomes.
“As organisations deploy more AI applications, they are realising that success depends on having the right data foundation, strong governance, and the flexibility to run workloads across hybrid environments. The findings underscore that modernising data architectures is a business imperative for organisations looking to bring trusted AI to their data, wherever it resides, while navigating the evolving demands of security, compliance, and growth,” he said.
Governance emerges as a key challenge
The survey also points to growing complexity around data governance as AI adoption expands. 73% of respondents said AI has made data governance more complex, while 55% reported delaying or cancelling more than six AI projects over the past 12 months because of governance, compliance or regulatory challenges.
The distributed nature of enterprise data adds to this challenge. 97% of respondents said they move data between environments at least monthly, highlighting the need for consistent governance across public and private clouds, on-premises infrastructure and edge environments.
Hybrid architectures gain ground
Enterprises are increasingly using hybrid architectures to balance performance, governance, cost and flexibility. 66% of respondents said they had moved AI workloads from public cloud environments back to private cloud or on-premises infrastructure during the past year.
Looking ahead, 25% said they plan to prioritise a hybrid-first architecture over the next two years, indicating a move away from dependence on a single infrastructure environment for enterprise AI workloads.
The report suggests that as AI adoption becomes increasingly widespread, organisations will focus more on optimising how AI workloads are deployed, governed and connected to enterprise data. Modernising data architectures and maintaining consistent governance across distributed environments are expected to become central to scaling AI securely and efficiently.
The survey was commissioned by Cloudera and conducted by Wakefield Research between June 5 and June 22, 2026. It covered 1,500 enterprise architects, cloud infrastructure leads and data architects across nine markets in the Americas, EMEA and APAC.