Cloudera, a provider of data management and AI software for enterprise environments, has released its 2026 State of Enterprise AI report, examining the cost, governance and data sovereignty challenges affecting AI adoption.
Based on a survey commissioned by Cloudera and fielded by Wakefield Research of 1,500 global IT leaders and decision-makers in September 2026, the report finds that the rules of enterprise AI are changing as rising costs, governance demands, and sovereignty requirements reshape how and where organizations run AI. Nearly nine in ten (89%) respondents have already limited or redesigned AI use cases because of rising token consumption. And 84% say data residency, sovereignty, or jurisdiction-specific requirements influence where AI workloads are deployed, underscoring the need for greater flexibility and control as enterprises scale AI.
Among the report’s key findings:
AI in production requires adjustment: 98% have pulled back an AI deployment due to failure, hallucinations, or unexpected behavior.
Governance is constraining scale: 75% cite governance and compliance as a constraint on scaling AI, while 55% report faster-than-expected growth in governance and compliance costs.
AI costs are reshaping strategy: 45% have moved AI workloads in response to higher or more volatile costs.
Sovereignty is shaping workload placement: 84% say residency or sovereignty requirements influence where AI runs, and 58% say moving workloads requires moderate or major redesign.
“Scale is exposing a new reality for enterprise AI: what works today may not make economic or operational sense tomorrow,” said Brian Martin, CTO of Applied AI at Cloudera. “Costs change, models evolve, regulations shift, and the right place to run a workload changes with them. Leaders need an AI strategy built for that reality, one that gives them the freedom to adapt without giving up control of their data, governance, or spend.”
The findings also reveal a growing focus on the foundations required for long-term AI success. If given the opportunity to restart their AI journey, 49% of respondents say they would strengthen governance from the beginning, 46% would invest in data quality earlier, and 45% would modernize infrastructure sooner. Another 45% would invest more in employee training.
This need for adaptability is making flexibility across environments increasingly important. Organizations cite resilience (42%), sovereignty and residency requirements (38%), cost reduction (38%), and proximity to data (37%) among the leading reasons for operating AI workloads across multiple environments.
Cloudera enables organizations to bring AI to their data anywhere it lives while maintaining consistent governance and control across environments. By bringing compute to governed data rather than requiring enterprises to move data to AI, organizations can choose where workloads run based on changing cost, performance, sovereignty, and business requirements while maintaining control across the AI lifecycle.
Download the full State of Enterprise AI 2026: The New Rules of Scale report to explore how enterprises are adapting their AI strategies as cost, governance, and sovereignty requirements reshape the path to scale. The findings will also take center stage at Cloudera EVOLVE NYC, where industry experts will discuss what it takes to build and operate AI as requirements continue to change.
