AI Infrastructure Financing Can Fake Demand
Supplier-backed capital can make infrastructure demand look stronger than the workloads beneath it. Fund measured utilization, not market optimism.
Read more →Supplier-backed capital can make infrastructure demand look stronger than the workloads beneath it. Fund measured utilization, not market optimism.
Read more →AI agents may erase much of the SaaS interface, but strong systems of record and workflow engines become more valuable as a result.
Read more →Enterprise AI agents fail in the gaps between systems, permissions, and people. Operators need repeatable crash-test environments before granting autonomy.
Read more →The model is rarely the whole bottleneck. Agent economics depend on the tool calls, orchestration, retries, and approvals around it.
Read more →Thomson Reuters spent $40 million to build its own AI model. The lesson for operators is not to copy the investment. It is to understand the conditions that made ownership rational.
Read more →Verizon’s AI now handles most inbound consumer calls and chats. The real lesson is the multi-year data consolidation that came first.
Read more →A $16,000 local AI cluster can keep data private. That still does not make it a sound business decision. Start with the workload, not the hardware.
Read more →The second largest GDPR fine in history was not about a data breach. It punished automated decisions nobody explained. Operators everywhere should take notes.
Read more →Customers’ AI assistants will soon draft their support messages. Fluent tickets are about to stop being a signal of anything.
Read more →New data puts a number on the resolution gap: fast AI answers, unresolved issues, and trust lost at the handoff. Here is how to actually close it.
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