Zscaler in the AI stack

The business and what the filings show

Zscaler runs a cloud security service, the Zero Trust Exchange, that sits between users, devices and workloads and the applications they reach, inspecting traffic and enforcing policy. Over its latest four quarters it reported $3.4B of revenue, +25% on the year before, at a 77% gross margin and a −4% operating margin; free cash flow was $852M, 25% of revenue, and remaining performance obligations $7.4B, 2.2 times its revenue.

Its 10-K frames AI as a new kind of traffic: AI agents reaching applications, models and data “at machine speed”, creating governance and data-security problems that older network tools were not built for. Zscaler sells “Security for AI”, controls over which AI applications employees use, what data reaches them and how agents connect, alongside AI in its own threat detection.

Zscaler shows a pattern common in security software: thin or negative operating margins under GAAP, alongside strong free cash flow, the difference being mostly stock-based compensation. The AI question is whether securing AI usage becomes a meaningful new product line or folds into the platforms of larger rivals.

How AI shows up in the numbers

AI shows up at Zscaler as more traffic to inspect, from employees using AI applications and from agents acting on their behalf, and as products sold to govern that traffic. Its filings do not separate AI revenue, so growth and remaining performance obligations are the read, along with how specific its earnings releases are about AI security sales.

For scale, Zscaler’s revenue over the latest four quarters equals 1% 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 Zscaler’s revenue grew +25%: 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 September 3, 2026, Zscaler mentioned AI 8 times in 1,426 words of narrative text, about 5.6 mentions per 1,000 words. Of its 5 sentences about AI, 0 included a number: a revenue figure, a growth rate, a customer count or another measurable result. Across the 8 releases we read, back to December 2, 2024, AI mentions per 1,000 words went from 3.5 to 5.6.

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.

• “AI represents one of the most significant opportunities in Zscaler's history.”
• “By connecting users, workloads, branches, and now agents directly to the applications they need without placing them on the network, we are uniquely equipped to help companie s both combat the threats created by agentic AI and securely deploy AI ag ents and models," said Jay Chaudhry, CEO, Chairman and Founder of Zs…”

Source: earnings release (Form 8-K, Exhibit 99.1), September 3, 2026.

The trend in the numbers

Since the start of 2023, Zscaler’s largest quarter by revenue was Q2 2026 at $898M, and its highest gross margin was 79% in Q1 2024. The latest quarter set the revenue record for the period.

Quarter by quarter, Zscaler’s revenue grew +26% in Q3 2025, +26% in Q4 2025, +25% in Q1 2026, +25% in Q2 2026 on the same quarter a year earlier. The pace has been steady.

Gross margin in the latest quarter was 77%, against 76% a year earlier, little changed. Operating margin moved from −4% to −2% over the same span. Over the latest four quarters it turned 34% of its revenue into operating cash flow and spent 8% of revenue on capital projects, against 6% a year earlier.

Where it sits in the stack

Zscaler sits in the software and applications layer of the AI stack. It sits at the top of the stack, where revenue from end customers has to come from; its own spending flows to AI clouds.

Among the 27 companies in this layer on our map, it ranks number 16 by revenue and number 9 of 27 by revenue growth. Its gross margin of 77% compares with 78% for the layer as a whole, close to the layer average. The full layer analysis is on the software 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 27 US-listed companies in its layer, Zscaler grew +25% over the latest year versus +19% for the layer combined, and converted 25% of revenue into free cash flow versus 33% for the layer. It is taking share of the layer’s revenue.

What has to go right, and what could go wrong

What has to go right. Companies have to route their AI traffic, from employees and agents, through a security layer they buy separately, and Zscaler has to be that layer.

What could go wrong. If the clouds, identity vendors or Palo Alto Networks bundle AI traffic controls into products customers already own, Zscaler’s AI opportunity could be smaller than the traffic growth suggests.

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 Zscaler’s layer is “AI challenges traditional SaaS assumptions”: Per-seat pricing, zero marginal cost, smooth ARR curves, and automatic land-and-expand break down when software does work on your behalf. The mistake is not using SaaS instincts. It is using them automatically.

The question it asks of any company is: What work is this product actually doing, and how does pricing map to it? Applied to Zscaler, 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.

• “$ 2,167,771 100 % Significant Customers No customer accounted for 10% or more of total revenue during the periods presented.” 10-K, September 3, 2026

Commitments and backlog

• Backlog. Zscaler reports $7.4B of remaining performance obligations, 2.2 times its revenue over the latest four quarters: contracted revenue not yet earned.
• Purchase commitments. $28M of unconditional purchase obligations as of July 31, 2026 (10-K): what it has contracted to buy from its own suppliers.

What to watch

Zscaler’s next quarterly report will cover the quarter ending around October 30, 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 29, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• Revenue growth against the layer, and whether AI security products lift it.
• Remaining performance obligations, which run well ahead of a year’s revenue.
• Operating margin against free cash flow margin, to see how much of the gap is stock-based compensation.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from Zscaler’s SEC filings, latest period ended July 31, 2026. Other companies: all company pages.