{"id":371372,"date":"2026-07-24T20:14:22","date_gmt":"2026-07-24T14:44:22","guid":{"rendered":"https:\/\/ebiztoday.news\/?p=371372"},"modified":"2026-07-24T20:14:22","modified_gmt":"2026-07-24T14:44:22","slug":"tokenomics-defines-agentic-ai-economics","status":"publish","type":"post","link":"https:\/\/ebiztoday.news\/index.php\/2026\/07\/24\/tokenomics-defines-agentic-ai-economics\/","title":{"rendered":"Tokenomics defines agentic AI economics"},"content":{"rendered":"
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The transition from chatbots to autonomous agents is changing the form of demand itself, and tokenomics \u2014 the economics of AI token consumption \u2014 is emerging because 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, in response to Jeetu Patel<\/a> (pictured), president and chief product officer of Cisco Systems Inc.<\/p>\n

\u201cThere\u2019s lower than 1% of the world that\u2019s using agents,\u201d Patel said. \u201cWhen you imagine that agents are literally a step function improvement from a chatbot, where you possibly can even have either your personal productivity or your organization\u2019s productivity materially change because of this of agents, I don\u2019t see the way you don\u2019t stay in a continued form of supply shortage for a reasonably very long time period.\u201d<\/p>\n

Patel spoke with theCUBE\u2019s Dave Vellante<\/a> on the\u00a0AMD Advancing AI event<\/a>, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed distributed inference, tokenomics and the shifting economics of agentic AI deployment. (* Disclosure below.)<\/em><\/p>\n

Tokenomics emerges because the defining constraint on agentic AI<\/h3>\n

Unlike chatbots, agents don\u2019t wait for a human prompt \u2014 they run constantly and increasingly discuss with other agents, which is pushing a brand new class of machine dedicated purely to agent workloads, Patel explained. Cisco\u2019s answer is Cisco Cloud Control, a unified management plane built to trace that sprawl across every location inference can occur.<\/p>\n

\u201cIt will possibly exit and have a look at your entire inferencing capability that you could have within the cloud, the entire inferencing capability you would possibly have in a non-public data center, in addition to your endpoint devices, in a single management plane,\u201d Patel said. \u201cInside that hybrid inference model, AMD handles intelligent routing and compute while Cisco supplies network bandwidth, security and what Patel called tokenomics \u2014 visibility into which agents are consuming tokens and whether that usage has grow to be excessive.\u201d<\/p>\n

Enterprises are also being pushed toward smaller, task-specific models to maintain costs in check fairly than defaulting to frontier systems for each job. Cisco recently released Antares<\/a>, a family of open-weight models built specifically to locate vulnerabilities in code without sending proprietary data to the cloud, a direct example of that routing logic in practice, Patel noted.<\/p>\n

\u201cThat individual announcement doesn\u2019t mean that we actually don\u2019t partner very deeply with Anthropic and with OpenAI,\u201d Patel said. \u201cIt just implies that you\u2019re going to want to have [small language models] that you should have control over. If I can find 70% of the vulnerabilities that way, great. And the remaining 30% I can find with a frontier model.\u201d<\/p>\n

Ease of use, not compute, stays the most important barrier to broader agent adoption. The technology still has to travel a protracted distance before it reaches extraordinary users the way in which the web once did, Patel noted.<\/p>\n

\u201cWe\u2019re moving at a reasonably fast pace, but we\u2019re nowhere near the extent of simplicity that\u2019s needed for eight billion people all going out and activating 1000’s of agents,\u201d he said.<\/p>\n

Here\u2019s the whole video interview, a part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of the\u00a0AMD Advancing AI event<\/a>:<\/p>\n