Cisco Systems (NASDAQ: CSCO) closed fiscal 2026 with record revenue of $63.3 billion, up 12% year over year, while non-GAAP EPS rose 14% to $4.33. Fourth-quarter revenue reached $17.3 billion, an 18% increase, with product revenue climbing 24%. Networking was a major contributor, posting 28% growth, while security revenue increased 14%.
Heading into fiscal 2027, Cisco expects revenue between $72.2 billion and $73.4 billion.
AI infrastructure is playing a growing role in that momentum. Hyperscaler AI infrastructure orders reached $9.3 billion for the year, roughly 4.5 times the fiscal 2025 total, while enterprise customers increased spending on private data center networks for AI workloads.
The company is also bringing AI into network management and internal support operations, showing how the technology is changing the infrastructure customers buy and the way Cisco runs its own business.
Why It Matters: AI infrastructure is placing new demands on networking, with decisions around workload location and token economics influencing data center architecture. Cisco is seeing customers prepare networks for AI while adding tools that let AI agents troubleshoot infrastructure and handle operational work. Its experience with Circuit and AI-based support also provides concrete results from deploying these systems in production workflows.
- AI Is Creating a Network Capacity Problem: Cisco booked $4 billion in hyperscaler AI infrastructure orders in Q4 and expects $7.5 billion in hyperscale AI infrastructure revenue during fiscal 2027. Chair and CEO Chuck Robbins said, “We believe the accelerating adoption of agentic AI is fueling a networking super cycle.” One reason is the amount of traffic generated when AI clusters span facilities. Cisco estimates AI-based scale-across traffic can be roughly 14 times that of traditional data center interconnect, increasing the importance of high-capacity networking between distributed GPU clusters.
- Private AI Is Starting to Influence Enterprise Architecture: Nexus switch orders tagged for AI deployments rose more than 85% sequentially, while data center networking orders increased more than 35% year over year. Management described customers weighing token costs and data sovereignty when deciding whether workloads belong in the cloud or on company infrastructure. That decision has consequences for private data center investment because local AI deployments require GPU connectivity alongside the infrastructure needed to operate those environments.
- AI Agents Are Moving Into the Network Operations Layer: Cisco Cloud Control gives customers a single management plane and unified data layer, with AI Canvas handling natural-language interaction with infrastructure data. Nearly 4,500 enterprises had signed up by the earnings call. Cisco described a network engineer who spent more than eight hours investigating dropped video calls before AI Canvas isolated the affected access point and root cause within minutes. The use case moves AI from generating information to diagnosing live infrastructure problems.
- AI Adoption Is Changing the Security Problem: Cisco said customers are seeking unified protection across users and agents, contributing to adoption of AI Defense and Guardrails in Secure Access. The company also introduced Antares, a family of open-weight small language models designed to identify known vulnerabilities in source code. Quantum preparation is entering the infrastructure discussion too, with post-quantum cryptography support available in newer Cisco routers and firewall platforms.
- Cisco’s Internal AI Deployment Offers a Measurable Operating Case: AI resolved 145,000 support cases without human intervention during fiscal 2026. Circuit, Cisco’s proprietary on-premise AI assistant, processed more than 75 million prompts in Q4 and runs on the company’s secure AI factory infrastructure. The system routes tasks to an appropriate large language model while managing GPU utilization and token consumption. That architecture connects model choice directly with the economics of running enterprise AI.
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