venturebeat
5% GPU utilization: The $401 billion AI infrastructure problem enterprises can't keep ignoring

For the last 24 months, one narrative justified every over-provisioned data center and bloated IT budget: the GPU scramble. Silicon was the new oil, and H100s traded like contraband. Reserve capacity now or your enterprise would be left behind.The bill is now due, and the CFO is paying attention. Gartner estimates AI infrastructure is adding $401 billion in new spending this year. Real-world audits tell a darker story: average GPU utilization in the enterprise is stuck at 5%. That utilization floor is driven by a self-reinforcing procurement loop that makes idle GPUs nearly impossible to release. What makes this shift more urgent is the CapEx reality now hitting enterprise balance sheets. Many organizations locked in GPU capacity under traditional three- to five-year depreciation cycles, [...]

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venturebeat
The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model [...]

Match Score: 243.51

venturebeat
FOMO is why enterprises pay for GPUs they don't use — and why prices keep climbing

Enterprises can't fix their GPU waste problem because the fix makes the problem worse. Releasing idle capacity would improve utilization, but the same shortage driving GPU prices up is exactly wh [...]

Match Score: 235.28

venturebeat
Cheaper tokens, bigger bills: The new math of AI infrastructure

Presented by NutanixAs enterprises move from AI experimentation into production deployment, the primary cost driver has shifted away from foundation model training and toward the infrastructure requir [...]

Match Score: 117.35

venturebeat
Wall Street is debating the AI buildout. Enterprises just answered: 86% say their GPUs run at half capacity or less

Enterprise companies are running AI agents ahead of the controls needed to manage them — and they deployed that way knowingly. That is the central finding from VentureBeat Research's June surve [...]

Match Score: 108.82

venturebeat
ScaleOps' new AI Infra Product slashes GPU costs for self-hosted enterprise LLMs by 50% for early adopters

ScaleOps has expanded its cloud resource management platform with a new product aimed at enterprises operating self-hosted large language models (LLMs) and GPU-based AI applications. The AI Infra Prod [...]

Match Score: 99.58

venturebeat
TrueFoundry launches TrueFailover to automatically reroute enterprise AI traffic during model outages

When OpenAI went down in December, one of TrueFoundry’s customers faced a crisis that had nothing to do with chatbots or content generation. The company uses large language models to help refill pre [...]

Match Score: 94.39

venturebeat
The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context sourc [...]

Match Score: 94.37

venturebeat
The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials

Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incide [...]

Match Score: 85.44

Destination
How to buy a GPU in 2025

One of the trickiest parts of any new computer build or upgrade is finding the right video card. In a gaming PC, the GPU is easily the most important component, and you can hamstring your experience b [...]

Match Score: 83.65