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Enterprise Survey Finds 93% Are Repatriating AI Workloads or Evaluating a Move Away from Public Cloud

Data sovereignty, cost overruns, and real-time performance demands drive growing enterprise adoption of on-premises AI infrastructure

This survey confirms what our customers say: when sensitive data, predictable costs, and real-time performance matter, on-premises AI delivers advantages that public cloud alone cannot match.””
— Jon Toor

SAN MATEO, CA, UNITED STATES, March 3, 2026 /EINPresswire.com/ — A new independent survey of 203 enterprise IT decision-makers reveals that the era of cloud-first AI strategies is giving way to a more deliberate, workload-driven approach. According to the Enterprise AI Infrastructure Survey 2026, commissioned by Cloudian, 93% of enterprises have already repatriated some AI workloads from public cloud, are in the process of doing so, or are actively evaluating repatriation. Nearly four in five (79%) have already moved workloads, while 73% plan to further shift toward on-premises or hybrid infrastructure over the next two years.

The survey, conducted in February 2026 via the Centiment research platform, identified three converging forces driving enterprise adoption of on-premises AI: data sovereignty concerns, cloud cost unpredictability, and real-time performance requirements.

Key Findings
Data sovereignty is the top driver of on-premises adoption. When deploying AI involving sensitive company data, 91% of respondents would choose on-premises, private cloud, or hybrid infrastructure over public cloud. Meanwhile, 74% flagged shadow AI—the unauthorized use of cloud AI tools by employees—as a critical or significant security concern, and 58% reported that data residency concerns have directly delayed or scaled back AI initiatives.

Cloud AI costs are exceeding expectations. Forty percent of enterprises report that actual cloud AI spending exceeds initial projections. Nearly half cite cloud-specific cost unpredictability—including difficulty forecasting total cost of ownership and consumption-based pricing fluctuations—as a barrier to expanding AI adoption.

Performance demands favor on-premises deployment. Three-quarters (75%) of respondents identified current or planned AI workloads that require or would benefit from on-premises infrastructure for acceptable latency performance. Use cases include real-time video analytics, manufacturing quality control, and low-latency transaction processing.

AI budgets are growing to fund this shift. Eighty-six percent of respondents expect their AI budgets to increase in 2026, with 40% projecting increases of 25% or more. Combined with the infrastructure shift toward on-premises and hybrid models, these budget increases signal significant enterprise investment in on-premises AI infrastructure over the coming year.

“Enterprises aren’t abandoning the cloud—they’re getting smarter about where AI workloads belong,” said Jon Toor, CMO at Cloudian. “This survey confirms what we’re hearing from customers every day: when sensitive data, predictable costs, and real-time performance matter, on-premises AI infrastructure delivers advantages that public cloud alone cannot match.”

Report Availability
The full Enterprise AI Infrastructure Survey 2026 report, including detailed methodology, charts, and analysis across all findings, is available for download at cloudian.com/lp/ai-survey-report.

Survey Methodology
The survey was conducted in February 2026 via the Centiment research platform. A total of 203 qualified respondents completed the survey, all screened for decision-making authority over AI strategy, investments, or infrastructure. Respondents represented a cross-section of enterprise industries including technology, manufacturing, retail, financial services, healthcare, and government. Two-thirds (66%) have AI applications running in production.

Jon Toor
Cloudian
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