AI is Reshaping the Technology Landscape. Is your Network Ready?

Is your Network AI-Ready?

When AI Scales, Networks Become the Differentiator

AI is fundamentally transforming the business landscape, driving massive changes in network traffic, complexity, and security demands. As AI accelerates workforce automation and machine-speed operations, networks face surging volumes of data, increased telemetry, and a broader attack surface.

These, amongst other factors, mean organisations need a network that is purpose-built for the AI era—one that meets the scale, speed, complexity, and security requirements of today and tomorrow.

How to meet the demands of the new era of AI networking

Meeting the requirements of the AI era means a new level of hyper-resilience is vital — delivering unprecedented bandwidth, energy efficiency, performance, and automation — across data center, core, and edge environments.

Cisco is leading the way with a validated, adaptive, and unified architecture approach to AI networking, introducing breakthrough infrastructure and management solutions that enable organisations to scale seamlessly, optimise performance, and unlock the full potential of next-generation AI workloads.

To move towards hyper-resilience and meet the demands of AI, a few things are essential:

High-bandwidth switches to handle the transition to 1.6-terabit speeds.
Advanced thermal management, including liquid cooling, to handle unprecedented power density.
Open networking architectures that support power-efficient optics. 
Deep-buffer routers that absorb bursts and prevent packet loss for connecting distributed data centers.
Carrier-grade software that scales seamlessly across the core and the edge.

At Cisco Live in Amsterdam earlier this year, Cisco announced several additions to its Agile Services Networking architecture to support AI connectivity requirements.

The advancements span breakthrough switching and routing platforms, advanced thermal management, and open, power-efficient architectures, responding to the demands of AI and setting new standards for what’s possible with AI infrastructure.

Scalable performance measurement for AI workloads now embedded in hardware fabric

AI workloads are highly sensitive to latency variation and congestion and often rely on deterministic path selection across massive IP transport fabrics. In these environments, understanding performance per individual path—not just per aggregate—is essential.

Recognising these evolving demands, Cisco has pioneered Integrated Performance Measurement (IPM). This innovative approach embeds performance measurement directly into the network hardware fabric, delivering a new era of scale, richness, and cost-efficiency in network performance monitoring.

Cisco Crosswork Network Automation enhanced with agentic AI

Building on the robust foundation of real-time, per-path network intelligence, combined with trusted, cross-domain data to train models, Cisco is extending intelligence and AI directly into the heart of network operations.

With the introduction of a multi-agentic AI framework, organizations can move beyond basic scripted automation towards human-assisted autonomy and on their way to full autonomy. This will enable a self-healing, self-optimizing infrastructure that doesn’t just report issues, but understands and adapts to prevent or fix issues as they arise. Through multi-agentic AI frameworks, network teams can manage complex, multi-vendor networks with greater speed, accuracy, and confidence.

Cisco has introduced enhanced agentic AIOps capabilities that tackle the most persistent challenges in managing modern networks:

Risk factor identification: In large-scale networks, multiple small, benign factors can combine to create a harmful situation that causes network issues like connection failures. These failures are hard to detect, especially in complex environments. AI analyses network event data and operational factors to identify common factors during these network events. This reduces mean time to identify (MTTI) and helps prevent widespread downtime by catching issues early.

Configuration drift detection: Small, untracked changes can silently undermine network stability by causing configurations to drift from their intended state. AI learns what normal looks like, so it can intuitively flag unexpected variances without needing a golden config baseline, highlighting what the correct configuration should be. This proactive approach reduces operational risks and downtime and is complementary to existing configuration management processes.

By aligning breakthrough hardware, integrated performance measurement, and AIOps capabilities, Cisco is creating the blueprint to drive ease and efficiency across the entire network lifecycle. This isn’t just about managing devices, but about creating a resilient, intelligent foundation that powers the AI era with zero friction.

C5 Technology and Cisco – Partnering to meet the demands of the AI era

Note: Information in this article has been sourced from Cisco. To learn more, visit:

As a Cisco Gold Partner, C5 Technology offers specialist expertise across Cisco’s suite of industry-leading AI and Networking solutions.
Contact C5 to learn more.