Cisco in the AI stack

The business and what the filings show

Cisco is the largest company in the networking layer by revenue: $63.3B over its latest four quarters, +12%, at a 65% gross margin and a 24% operating margin. Most of that still comes from enterprises, governments and telecom carriers rather than from AI data centers, which is why its growth looks modest next to the specialists in this layer.

Its AI exposure comes through two routes. It sells switches, routers and its own Silicon One chips to hyperscalers building AI networks, and its 10-K says it entered into additional purchase commitments in fiscal 2025 and 2026 to meet expected demand from them. It also sells networking for enterprises that are starting to run AI in their own data centers. Remaining performance obligations were $46.7B.

Cisco is the comparison point for every networking specialist on this map. If AI networks become a larger share of what hyperscalers buy, Cisco has to win a meaningful share of them to keep pace with Arista and Nvidia; if enterprises follow the hyperscalers into AI, Cisco’s installed base gives it an advantage no newer company has.

How AI shows up in the numbers

For Cisco, AI is a growing part of a large, mature business rather than the whole story. Sales of AI infrastructure to hyperscalers show up in its service provider and cloud market, which its 10-K warns is volatile and concentrated among few customers. The enterprise side, where Cisco is strongest, is where AI networking demand is earliest, so its results lag the specialists on the way up and may hold up better if hyperscaler spending slows.

For scale, Cisco’s revenue over the latest four quarters equals 11% of the $566B the five largest buyers spent on capital projects over their latest four quarters. Their capex rose +81% on the year before, while Cisco’s revenue grew +12%: slower than the spending, so it is capturing a smaller share of each new capex dollar, or more of its business sits outside the build-out.

How it talks about AI

In its latest earnings release, furnished to the SEC on August 12, 2026, Cisco mentioned AI 2 times in 1,656 words of narrative text, about 1.2 mentions per 1,000 words. Of its 2 sentences about AI, 1 included a number: a revenue figure, a growth rate, a customer count or another measurable result. Across the 8 releases we read, back to November 13, 2024, AI mentions per 1,000 words went from 0.9 to 1.2.

Specific claims are easier to check against the numbers than general enthusiasm, which is why the share of AI sentences that carry a figure is worth watching alongside how often AI is mentioned. The sentences below are quoted from the release as published, after removing safe-harbor text and company boilerplate.

• “Significant momentum and raised expectations for AI infrastructure from hyperscalers ◦ $4 billion of orders taken in Q4, bringing the total for FY 2026 to $9.3 billion ◦ Delivered approximately $4 billion of revenue in FY 2026; $7.5 billion expected in FY 2027”
• “With the breadth and depth of our portfolio and our competitive differentiation in secure networking, Cisco is well positioned to support our customers however or wherever they decide to deploy AI.”

Source: earnings release (Form 8-K, Exhibit 99.1), August 12, 2026.

The trend in the numbers

Since the start of 2023, Cisco’s largest quarter by revenue was Q2 2026 at $17.3B, and its highest gross margin was 66% in Q3 2024. The latest quarter set the revenue record for the period.

Quarter by quarter, Cisco’s revenue grew +8% in Q3 2025, +10% in Q4 2025, +12% in Q1 2026, +18% in Q2 2026 on the same quarter a year earlier. Growth has been accelerating.

Gross margin in the latest quarter was 64%, against 63% a year earlier, little changed. Operating margin moved from 21% to 25% over the same span. Over the latest four quarters it turned 22% of its revenue into operating cash flow and spent 2% of revenue on capital projects, against 2% a year earlier.

Where it sits in the stack

Cisco sits in the networking and optics layer of the AI stack. It is paid by the AI clouds and servers layers; its own spending flows to chips, foundry & tools.

Among the 10 companies in this layer on our map, it ranks first by revenue and number 10 of 10 by revenue growth. Its gross margin of 65% compares with 53% for the layer as a whole, a sign that it keeps more of each dollar than its neighbors. The full layer analysis is on the networking page.

Latest four quarters for 10-Q filers; latest fiscal year for 20-F filers. Companies under $100 million of revenue are left out.

Against the 10 US-listed companies in its layer, Cisco grew +12% over the latest year versus +25% for the layer combined, and converted 20% of revenue into free cash flow versus 19% for the layer. It is growing more slowly than its layer, so its share of the layer’s revenue is shrinking.

What has to go right, and what could go wrong

What has to go right. Cisco has to win a meaningful share of hyperscalers’ AI networks with its own silicon, and enterprises have to start building AI infrastructure of their own on Cisco equipment.

What could go wrong. Hyperscalers could keep buying mostly from Arista, Nvidia and white-box suppliers, leaving Cisco growing with the slower enterprise market while its purchase commitments rise.

These describe the conditions the business depends on, as the filings show them. They are not a view on the stock.

Through the lens of Investing in AI

Rob May’s book offers six mental models for telling AI moats from traps. The one most useful for Cisco’s layer is “AI is a collection of technologies”: Neural nets, Bayesian methods, symbolic systems, and evolutionary algorithms have different cost structures, moats, and risks. Treating AI as one bucket hides the differences that matter. Invest in defensibility, not in a single paradigm.

The question it asks of any company is: What kind of AI is this, and how hard is it to replicate? Applied to Cisco, the filings on this page are the place to start: the margin trend shows whether it holds scarce value or passes it through, the customer and financing disclosures show who it depends on, and the commitments show what it has promised before the revenue arrives.

Customers and concentration

US companies must disclose any customer that accounts for 10% or more of revenue, and foreign filers usually describe their largest customers. Concentration matters because a company’s growth is only as durable as the handful of buyers behind it, and in the AI stack those buyers are often the same few companies.

• “No single customer accounted for 10% or more of revenue in fiscal 2025 or 2024.” 10-K, September 2, 2026

Commitments and backlog

• Backlog. Cisco reports $46.7B of remaining performance obligations, 0.7 times its revenue over the latest four quarters: contracted revenue not yet earned.

What to watch

Cisco’s next quarterly report will cover the quarter ending around October 24, 2026. Large companies must file a 10-Q within 40 days of a quarter’s end and a 10-K within 60 days of the fiscal year’s end, so the new figures should arrive by about December 23, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• What Cisco reports about AI infrastructure orders from hyperscalers, the part of the business that tracks the build-out.
• Gross margin as more revenue comes from large cloud customers, who usually negotiate harder than enterprises.
• Purchase commitments with contract manufacturers, which show how much demand Cisco is preparing for.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from Cisco’s SEC filings, latest period ended July 25, 2026. Other companies: all company pages.