Broadcom and Radius Tech Report: 97% of IT Leaders See Public Cloud Waste as Enterprises Shift AI Inference to Private Cloud
Survey shows a sharp drop in public cloud AI inference usage, driven by cost overruns and data sovereignty concerns pushing enterprises toward private architectures.
US semiconductor company Broadcom and market research firm Radius Tech have published the "Private Cloud Outlook 2026" report. Based on a survey of 1,800 senior IT decision-makers globally, it reveals a large-scale migration from public to private cloud as artificial intelligence enters its production phase.
The report indicates that cost management has replaced security concerns as the biggest worry for enterprises regarding public clouds. A staggering 97% of surveyed IT leaders stated that their companies experience budget waste in public cloud spending, with 52% estimating that more than a quarter of their spend is wasted. This is primarily because production-grade AI applications require continuous, uninterrupted operation, making GPU rentals, network bandwidth, and egress fees difficult to predict.
As agentic AI and large language models are deployed in daily business operations, the usage of public cloud for the AI inference stage dropped by 15 percentage points over the past year, falling from 56% to 41%. Meanwhile, the proportion of enterprises planning to increase private cloud investments over the next three years rose significantly from 51% to 72%, growing at twice the rate of public cloud.
This trend, known as "workload repatriation," is accelerating. 83% of enterprises are considering or have already started moving data and applications back to private clouds, with 50% having completed partial migrations, up 15 percentage points from 35% the previous year. Beyond traditional sectors like medical records, payment systems, and core databases, "AI models and inference" was listed as an independent repatriation category for the first time, included in 43% of repatriating enterprises.
The core logic driving this shift is summarized as the "3C model": predictable costs, reduced operational complexity due to talent shortages, and control over data sovereignty. 86% of IT leaders admitted that geopolitics and regulatory laws have substantially influenced their cloud strategies, particularly in high-compliance industries like finance and healthcare where data must remain local to meet sovereignty requirements.