AI infrastructure bottlenecks
As AI use broadens, companies are running into physical limits on compute and power, prompting rationing and higher prices for infrastructure capacity. Network and systems vendors are responding with new control and observability offerings, and some providers are pushing smaller on‑prem models to keep sensitive workloads inside company perimeters. (enterpriseai.economictimes.indiatimes.com (networkworld.com (businesstoday.in))
Artificial intelligence is running into old-world limits: power, chips, and data-center space are getting harder to secure. (enterpriseai.economictimes.indiatimes.com) The pressure is showing up in prices and delays. The Economic Times, citing The Wall Street Journal, reported on April 14 that companies are rationing access, Blackwell chip rentals have risen in recent months, and cloud providers are facing longer lead times for capacity. (enterpriseai.economictimes.indiatimes.com) A token is the unit providers use to meter artificial intelligence work, and more “agentic” tools mean more tokens consumed per task. Ben Pouladian told the publication that artificial intelligence is no longer just a chatbot query, while Vultr Chief Executive J J Kardwell said the capacity crunch is the worst he has seen in more than five years. (enterpriseai.economictimes.indiatimes.com) The hardware behind that demand is getting denser and harder to house. Nvidia says its GB200 NVL72 system packs 36 Grace central processing units and 72 Blackwell graphics processing units into one liquid-cooled rack, effectively turning a cabinet into a single giant computer. (nvidia.com) That changes what companies have to buy before they can scale. Nvidia says the rack is liquid-cooled and designed for trillion-parameter inference, so the bottleneck is no longer only chips but also cooling loops, power delivery, and floor-ready facilities. (nvidia.com) Vendors are moving to sell the control layer around that scarce hardware. Cisco said on March 16 that it expanded its Secure AI Factory with Nvidia so customers can run artificial intelligence from central data centers to factory floors, and on April 9 it said it would acquire Galileo Technologies to add observability for multi-agent systems into Splunk. (investor.cisco.com) (blogs.cisco.com) Network World reported on April 15 that Cisco’s latest push is to make the network and security stack the control plane for the “agentic” era. The article said Galileo gives Cisco a way to monitor how artificial intelligence agents behave, not just whether servers stay up. (networkworld.com) Some companies are responding by shrinking the model instead of expanding the cloud bill. Business Today reported on April 15 that AvenuesAI, through PhroneticAI, is building fully on-premise small language models with 1 billion to 10 billion parameters so client data stays inside the customer’s own systems. (businesstoday.in) AvenuesAI Chairman and Managing Director Vishal Mehta said companies are rethinking outside platforms because of data security, privacy, and sovereignty concerns. The report also pointed to a mid-2025 Nayara Energy dispute with Microsoft over suspended cloud and email services as a warning about dependence on external infrastructure. (businesstoday.in) The strain is also visible in reliability. The Economic Times said outages at Anthropic since mid-February pushed some enterprise customers to switch providers, and Anthropic’s public status page shows multiple incidents in April, including elevated errors on requests to Claude models on April 10. (enterpriseai.economictimes.indiatimes.com) (status.claude.com) The immediate fight in artificial intelligence is no longer only over better models. It is over who can get enough electricity, cooling, networking, and control software to keep those models running when more companies try to use them at once. (enterpriseai.economictimes.indiatimes.com) (networkworld.com)
