A new survey commissioned by Cloudian finds that enterprises are actively rebalancing their workload placement strategies. Rather than abandoning cloud entirely, organizations are becoming more deliberate about where data and workloads reside.
Data sovereignty has emerged as a critical driver in infrastructure decisions. Ninety-nine percent of respondents indicated it is at least a moderate factor, while 82% view it as a primary or significant driver. More than half (59%) expressed concerns about cloud providers accessing their data for analytics or model training, and 53% are bound by customer or partner contracts that restrict data residency.
Regulatory pressures are intensifying the challenge, with 45% of organizations experiencing new cross-border data restrictions in the past two years. This reflects the rapid evolution of data localization laws across regions such as the EU and Asia-Pacific.
The cost dynamics of public cloud have become increasingly challenging at scale. Eighty-four percent of respondents reported exceeding their cloud storage budgets, with nearly one in five surpassing them by more than 30%. The primary drivers include data egress fees, costs that escalate with data volume, and premium pricing for residency-compliant regions.
These economic realities are prompting organizations to reconsider defaulting to cloud for all workloads, particularly for large-scale or frequently accessed storage.
AI workloads are acting as a major catalyst for the move toward on-premises infrastructure. Eighty-five percent of respondents said AI requirements are influencing their infrastructure decisions. More than half cited challenges with cloud-based AI inference latency, while 52% need to keep AI training data on-premises for security or compliance reasons.
When ranking infrastructure priorities for the coming year, AI and ML infrastructure topped the list at 57%, followed closely by data sovereignty and security (56%) and cost predictability (54%).
“This isn’t a story about enterprises souring on cloud,” said Jon Toor, CMO of Cloudian. “It’s about organizations getting smarter about workload placement. The data makes clear that for sovereignty-sensitive, AI-intensive, and large-scale storage workloads, on-premises is often the better answer.”
“The compliance landscape has gotten materially more complex, and it’s moved faster than most cloud providers’ infrastructure footprints,” Toor added. “When your data residency requirements don’t map cleanly to available cloud regions, on-premises stops being a legacy option and starts being the only viable one.”
“AI is the forcing function. Organizations that might have tolerated suboptimal cloud economics or sovereignty workarounds for conventional workloads are finding they can’t accept those same tradeoffs for AI.”
The survey emphasizes that enterprises are not reversing course on cloud adoption. Approximately 30% are still expanding their cloud presence. Instead, organizations are pursuing a deliberate hybrid strategy, optimizing workload placement based on specific needs such as elasticity, cost predictability, latency, and data jurisdiction.
“Hybrid isn’t a compromise anymore, it’s a deliberate strategy,” Toor said. “The enterprises doing this well have gotten very precise about what goes where and why. Cloud for elastic, unpredictable demand. On-premises for everything where you need predictable cost, low latency, and clear data jurisdiction.”
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