As agentic AI inference surges, tokenomics becomes the enterprise’s defining budget constraint
The transition from chatbots to autonomous agents is changing the shape of demand itself, and tokenomics — the economics of AI token consumption — is emerging as the defining constraint on enterprise budgets as round-the-clock inference replaces intermittent usage. Fewer than 1% of potential users are currently deploying agents at scale, leaving enormous headroom for growth in inferencing demand, according to Jeetu Patel (pictured), president and chief product officer of Cisco Systems Inc.
“There’s less than 1% of the world that’s using agents,” Patel said. “If you believe that agents are actually a step function improvement from a chatbot, where you can actually have either your personal productivity or your company’s productivity materially change as a result of agents, I don’t see how you don’t stay in a continued kind of supply shortage for a pretty long time period.”
Patel spoke with theCUBE’s Dave Vellante at the AMD Advancing AI event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed distributed inference, tokenomics and the shifting economics of agentic AI deployment. (* Disclosure below.)
