Cloudera study finds 89% of enterprises redesign AI use cases amid rising costs

A global survey commissioned by Cloudera found that 89% of enterprises have limited or redesigned AI use cases because of rising token consumption, while 84% said data residency, sovereignty or jurisdictional requirements influence where AI workloads are deployed.

The State of Enterprise AI 2026: The New Rules of Scale report, conducted by Wakefield Research among 1,500 IT leaders and decision-makers, highlights rising costs, governance demands and regulatory requirements as constraints on enterprise AI deployment.

The survey found that 98% of respondents had pulled back an AI deployment due to failure, hallucinations or unexpected behaviour. Governance and compliance were cited as barriers to scaling by 75%, while 55% reported faster-than-expected growth in related costs. Meanwhile, 45% had moved AI workloads in response to higher or more volatile costs.

Sovereignty requirements are also affecting infrastructure decisions. While 84% said residency or sovereignty rules influence workload placement, 58% reported that moving workloads requires moderate or major redesign.

The findings indicate that enterprises are reassessing the foundations of AI deployment. If given the opportunity to restart their AI journey, 49% of respondents said they would strengthen governance earlier, 46% would invest in data quality, and 45% would modernise infrastructure and increase employee training.

Organisations cited resilience (42%), sovereignty and data residency (38%), cost reduction (38%) and proximity to data (37%) as key reasons for running AI workloads across multiple environments.

The report points to a growing need for enterprises to balance AI adoption with cost control, governance and the ability to move workloads as business and regulatory requirements change.