Conventional capability planning gained’t work within the period of agentic AI
As AI turns into core to enterprise operations, campus and department community architects are moving into new territory. The outdated playbooks for capability planning gained’t maintain within the age of agentic AI, the place autonomous methods work together, collaborate, and determine in ways in which defy conventional, predictable site visitors patterns.
Enterprise AI is now not confined to the info heart. AI fashions, inference, and autonomous agent-to-agent exchanges are actually working on the edge, on campuses, and in department networks. This shift is setting solely new necessities for visibility, adaptability, and capability planning.
After we’re now not in a position to predict capability, what does it imply to be AI-ready from a community perspective?
From consumer–server to agent–agent
Traditionally, enterprise networking adopted a consumer–server mannequin. Whether or not accessing SaaS, becoming a member of a video name, or querying inner CRM knowledge, site visitors flowed predictably between an endpoint and an outlined utility.
Agentic AI will upend this mannequin. With many-to-many conversations between autonomous brokers, these interactions could be steady, context-aware, and extremely variable, producing complicated east–west knowledge flows inside campuses and throughout branches.
Contemplate an workplace setting: AI-powered video analytics monitor safety and amenities. Cameras, sensors, and AI brokers course of foot site visitors knowledge domestically and within the cloud. When an agent detects uncommon crowding in a constructing, it triggers real-time coordination: safety alerts, HVAC changes, or employees notifications. The end result: a right away spike in lateral campus site visitors that’s each unpredictable and important.
Or from a department perspective, a retail financial institution instance: AI brokers watch over bodily safety, buyer circulation, and IT well being. An anomaly, for instance quite a few failed ATM transactions, prompts brokers throughout branches to share logs, safety feeds, and efficiency knowledge. This agent-to-agent change crosses not simply branches, but in addition cloud and knowledge heart hyperlinks, in site visitors bursts that defy legacy peak-planning fashions.
The tip of over-provisioning for peak site visitors?
Human-driven site visitors tends to comply with predictable day by day rhythms: peaks throughout enterprise hours and lulls in a single day. Autonomous AI site visitors behaves otherwise. Agent-to-agent “chatter” usually runs constantly, establishing a persistent baseline of exercise. On prime of that, sudden and localized bursts can erupt when AI methods detect an occasion and instantly coordinate a response. And in contrast to conventional site visitors patterns that focus on fastened functions, these surges will seem in solely totally different elements of the community from one second to the following.
This unpredictability means the problem will now not merely be about how a lot site visitors a community can carry general. It’s about the place, when, and the way rapidly capability should shift to satisfy real-time calls for.
A brand new method to capability planning
Usually, organizations provision for max anticipated load by counting on instruments like load balancers or CDNs to easy utilization. Within the AI edge period, that mannequin will break down. Information sovereignty, privateness, and low-latency necessities will drive extra native processing, a shift that can improve inter-site site visitors and make east–west flows vital to sustaining efficiency and resilience.
Merely including bandwidth in every single place gained’t be sensible nor cost-effective. As a substitute, networks should evolve to be elastic, dynamically reallocating assets as site visitors patterns change. Which means having application-aware networking able to figuring out and prioritizing agent-to-agent flows as they emerge, and utilizing dynamic path choice to maintain latency low whereas navigating unpredictable load shifts. It additionally means integrating safety tightly with id to protect towards dangers distinctive to autonomous methods, and investing in end-to-end visibility that goes past counting bytes to really perceive AI-driven site visitors connectivity.
Whereas we’re prone to see innovation and new options to alleviate among the burden of always-on AI workloads, reality stays that capability planning within the AI agent period will now not be about provisioning for a peak, however about designing for clever, real-time adaptation.
Intelligence is the brand new peak capability
Being AI-ready shouldn’t be about scaling up bandwidth; it’s about making the community as adaptable and context-aware because the AI methods it helps. The following technology of campus and department networks will likely be measured by how rapidly they will acknowledge, prioritize, and safe AI-driven flows — wherever, anytime, and in actual time.
