Cisco is cutting nearly 4,000 jobs and redirecting investment toward artificial intelligence infrastructure, signaling how the AI spending boom is rapidly transforming priorities across the global technology industry, far beyond semiconductor makers alone.
The networking giant said Wednesday the restructuring is designed to accelerate investment into high-growth areas tied to AI, including silicon, optics, cybersecurity, and internal AI deployment, as hyperscale cloud companies sharply increase spending on the infrastructure required to support large-scale AI systems.
The announcement sent Cisco shares soaring more than 16% in extended trading, reflecting investor confidence that the company is emerging as one of the major secondary beneficiaries of the AI arms race currently dominated by chipmakers such as Nvidia.
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Chief Executive Officer Chuck Robbins framed the restructuring as part of a broader strategic realignment around AI.
“The companies that will win in the AI era will be those with focus, urgency, and the discipline to continuously shift investment toward the areas where demand and long-term value creation are strongest,” Robbins said in a statement.
The layoffs, which represent less than 5% of Cisco’s global workforce, underscore a growing trend across Silicon Valley where companies are simultaneously investing aggressively in AI while reducing headcount in slower-growth or legacy business segments.
Cisco had approximately 86,200 employees as of late July. The company said the restructuring would cost up to $1 billion, with roughly $450 million recognized in the fourth quarter and the remainder spread into fiscal 2027.
The cuts come as investors increasingly reward companies tied to AI infrastructure expansion, particularly those positioned beyond the semiconductor layer itself.
While Nvidia has dominated attention because of the explosive demand for AI processors, the buildout of AI data centers is also creating enormous demand for networking hardware, high-speed switches, optical interconnects, and cybersecurity systems needed to move and manage massive quantities of data between servers.
Cisco is now emerging as a major beneficiary of that shift. The company disclosed it has secured $5.3 billion in AI infrastructure orders from hyperscalers so far this fiscal year and raised its full-year AI order outlook to $9 billion from a previous forecast of $5 billion.
The scale of the upward revision evidences how quickly AI-related capital expenditure is spreading through the technology supply chain.
Analysts say hyperscalers such as Microsoft, Amazon, Alphabet, and Meta Platforms are no longer spending only on AI chips themselves but increasingly on the broader infrastructure ecosystem required to scale generative AI systems.
Ryan Lee, Direxion’s senior vice president of product and strategy, said Cisco’s strong results reinforce the idea that hyperscaler spending is expanding beyond semiconductors.
“Though much will likely be made about a slight decrease in headcount, the post-market move we are seeing is truly the result of hyperscaler capex spilling downstream,” Lee said.
“This move validates that this capex is about more than just chips.”
That dynamic is becoming one of the defining themes of the global AI economy. Early investor focus centered almost entirely on chip suppliers because graphics processing units became the core bottleneck for training advanced AI models. But as AI systems scale, networking capacity is emerging as another critical constraint.
Large language models and AI inference systems require enormous bandwidth to transfer data efficiently across clusters of interconnected servers. That has increased demand for ultra-fast switching equipment and optical networking systems, areas where Cisco has longstanding expertise.
The company said networking product orders rose more than 50% in the third quarter compared with a year earlier, while data-center switching orders climbed over 40%. Those figures suggest AI infrastructure spending is beginning to reshape Cisco’s growth profile after years of relatively modest expansion in traditional enterprise networking markets.
On an earnings call, Cisco’s finance chief Mark Patterson said it was “reasonable” to expect at least $6 billion in AI hyperscale-related revenue in fiscal 2027. The guidance points to expectations that AI infrastructure spending will remain elevated for several years rather than representing a short-term investment cycle.
Cisco’s quarterly results also exceeded Wall Street expectations. Revenue for the quarter ended April 25 came in at $15.84 billion, above analyst estimates of $15.56 billion, according to LSEG data. The company raised its fiscal 2026 revenue forecast to between $62.8 billion and $63 billion, up from an earlier range of $61.2 billion to $61.7 billion.
The strong outlook helped extend Cisco’s stock rally. Shares are already up roughly 32% this year, reflecting growing investor belief that the company may be entering a new growth phase tied directly to the AI infrastructure buildout.
The broader significance of Cisco’s results lies in what they reveal about the next stage of the AI economy. The first wave of AI investment centered heavily on acquiring computing power. The next phase increasingly involves building the digital plumbing necessary to operate AI systems at an industrial scale. That includes networking equipment, data-center architecture, power systems, cooling infrastructure, and cybersecurity.