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Publication Date: 2026-03-18 15:00:00
Partner Content The enterprise AI question has shifted from “Can we build a chatbot?” to “Can we run agentic AI at scale with governance and cost we can defend?” Personalized digital assistants have conditioned people to expect systems that don’t just answer questions, but get things done. That same expectation is now landing inside the enterprise, where agentic systems can automate multi-step workflows, improve decisions across teams, and reshape how work gets done.
As agentic AI takes center stage, adoption has hit a tipping point. Success hinges less on model selection and more on the infrastructure needed to securely run thousands of agents.
This shift matters because agentic AI doesn’t scale like a chatbot or a single workload. A company-wide fleet of agents is a moving swarm of concurrent users, bringing with them bursts of demand, constant calls to data and tools, and a long tail of edge cases that quickly turn into incidents.
Enterprises need an operating environment that makes agentic systems safe and repeatable in the real world. This shift aligns with the rise of the AI factory: an environment purpose-built to deliver high-performance inference, shared services, governance, and cost control across the enterprise.
Speed vs. control: the agentic AI trade-off
Enterprises face a two-sided challenge as they scale agentic AI. AI developers get bogged down by disconnected tools, siloed…
