On November 12, Cisco announced that it now expects full-year revenue in the range of US$60.2 billion to US$61.0 billion, up from the previously guided US$59 billion to US$60 billion. The company also raised adjusted earnings-per-share estimates to US$4.08-4.14 from US$4.00-4.06, reflecting stronger than anticipated uptake of its high-performance networking gear by hyperscalers and enterprise clients.

Cisco said that, in fiscal 2025, it had secured more than US$2 billion in AI-specific infrastructure orders — nearly all of them from cloud and hyperscale providers — and expects the pipeline for fiscal 2026 to exceed US$3 billion. The company’s chief executive commented that the firm is now seeing “significant momentum” in networks designed to support large-scale AI models, edge computing deployments, and sovereign-cloud architectures.

The move underscores how the broader AI transformation is no longer just about chip makers and software platforms — it’s also rapidly driving demand for next-generation networking and infrastructure hardware. Cisco’s strategy positions it to capture a share of what many analysts call the “AI infrastructure arms-race”.

Key Highlights
• Cisco raised full-year revenue forecast to US$60.2-61.0 billion from US$59-60 billion.
• Adjusted EPS guidance upgraded to US$4.08-4.14 from US$4.00-4.06.
• AI-specific infrastructure orders surpassed US$2 billion in FY 2025 and are expected to grow further in FY 2026.
• Cisco is leveraging demand from hyperscalers, sovereign-cloud providers and enterprise edge-deployments to drive growth.
• The broader implication: networking hardware is a critical component of the AI ecosystem, not just chipsets and algorithms.

Why This Matters
• The elevated forecast signals that infrastructure build-out tied to AI is accelerating — not just in chips or data-centres, but in the network backbone that connects and powers them.
• Investors may refocus on companies like Cisco whose growth depends on hardware and systems — not just software or consumables — which could reshape tech sector rotation.
• Regions or firms with under-developed networking capacities may become bottlenecks in the AI rollout, creating strategic opportunities (and risks) for deployment and investment.
• For enterprises and governments, this trend highlights the need to evaluate network readiness as a key part of AI-maturity — not just compute or storage budgets.

Source:
Reuters – Full Article