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, [...]
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 [...]
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 [...]
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 [...]
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 [...]
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 [...]
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 [...]
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 [...]
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 [...]