Cisco is laying off nearly 4,000 employees while reporting record quarterly revenue of $18 billion. The company said the cuts will free up resources to invest more aggressively in AI infrastructure and networking products. The pattern is now familiar across the tech industry: record revenue, record profits, and fewer people needed to produce them.
What Happened
Cisco told the SEC it will eliminate approximately 3,900 positions — roughly 4.5 percent of its global workforce. CEO Chuck Robbins framed the cuts as a strategic rebalancing rather than a response to weakness. Revenue hit an all-time high. Demand for networking equipment that connects AI data centers is surging. And Cisco is redirecting the savings from the layoffs into AI-specific products and R&D.
The company is specifically investing in networking hardware optimized for AI infrastructure. As hyperscalers build massive GPU clusters to train and run AI models, the networking equipment that connects those chips becomes a critical bottleneck. Cisco wants to own that layer — selling the switches, routers, and fabric that ties together the TPU clusters, Graviton arrays, and GPU farms powering the AI economy.
The Pattern Keeps Repeating
Cisco joins a growing list of companies cutting jobs to fund AI while posting strong financial results. Cloudflare said AI made 1,100 positions obsolete even as revenue hit a record. Match Group froze hiring to redirect spending toward AI tools. Block laid off 40 percent of its workforce citing AI. Amazon cut 30,000 corporate positions while spending billions on AI infrastructure.
The common thread is that AI creates value while reducing headcount. Companies are earning more revenue with fewer employees. The productivity gains are real. The human cost is real too. Goldman Sachs estimates AI eliminates roughly 16,000 net jobs per month in the US. Cisco's 3,900 cuts add to that total.
Jensen Huang argues that AI creates an enormous number of new jobs. The data from individual companies tells a different story — at least in the near term. The jobs being created are different from the jobs being cut. AI engineers and infrastructure specialists are in demand. Administrative, support, and mid-level management roles are being automated or eliminated.
Why Networking Matters for AI
Cisco's AI bet is focused on the infrastructure layer. Training a frontier AI model requires thousands of chips working together in perfect coordination. The networking fabric that connects those chips — allowing them to share data at nanosecond speeds — determines how efficiently the entire system operates.
As AI data centers scale from thousands of chips to millions, the networking requirements grow exponentially. ASML makes the machines that produce the chips. Nvidia designs the chips themselves. Cisco wants to be the company that connects them all together.
The opportunity is significant. Every major cloud provider — Google, AWS, and Microsoft Azure — is building AI infrastructure at unprecedented scale. The networking hardware they need to connect that infrastructure is a multi-billion dollar market that Cisco is positioning to dominate.
The Bigger Picture
Cisco's layoffs are another data point in the AI economy's central contradiction. The technology creates enormous value. It generates record revenue. It makes companies more efficient and more profitable. And it does all of this while requiring fewer human employees.
For the 3,900 people losing their jobs, the record revenue number is irrelevant. For investors, the combination of higher revenue and lower headcount is exactly what they want. And for the broader workforce, the pattern raises the question that defines the AI era: if companies keep posting record results with fewer people, where do the people go?
Cisco does not have an answer. Neither does anyone else.
