AppLovin in the AI stack

The business and what the filings show

AppLovin runs an advertising platform for mobile apps, and increasingly for e-commerce, that matches ads to users with its machine-learning recommendation engine, Axon. It sold its own apps business on June 30, 2025 and presents it as discontinued operations, so the figures here are the advertising business alone. Over its latest four quarters it reported $6.8B of revenue, +61% on the year before, at an 88% gross margin and a 77% operating margin, the highest operating margin in the software layer.

AppLovin is the map’s clearest example of machine learning showing up directly in the income statement. It does not sell AI to customers as a product; it uses a model to decide which ad to show, and earns a share of the advertising spend that model makes more effective. When the model improves, revenue and margin can rise together, because the cost of serving each additional ad is small.

That also defines the risks. Its revenue depends on advertisers continuing to see returns, on access to the app stores and device platforms its ads run on, and on the expansion into e-commerce advertising. AppLovin does not tag capital spending or remaining performance obligations in the standard XBRL fields this map reads, so its free cash flow and backlog are not shown here.

How AI shows up in the numbers

For AppLovin, AI is the product’s engine rather than a feature: Axon’s recommendations are what advertisers pay for. That makes its revenue and margin a direct, if narrow, measure of what a better model is worth, and makes it one of the few companies on the map where AI’s effect on profit is visible without any separate disclosure.

For scale, AppLovin’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 AppLovin’s revenue grew +61%: 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 5, 2026, AppLovin mentioned AI 0 times in 339 words of narrative text, about 0.0 mentions per 1,000 words. Of its 0 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 November 6, 2024, AI mentions per 1,000 words went from 0.0 to 0.0.

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.

Source: earnings release (Form 8-K, Exhibit 99.1), August 5, 2026.

The trend in the numbers

Since the start of 2023, AppLovin’s largest quarter by revenue was Q2 2026 at $1.9B, and its highest gross margin was 89% in Q1 2026. The latest quarter set the revenue record for the period.

Quarter by quarter, AppLovin’s revenue grew +68% in Q3 2025, +66% in Q4 2025, +59% in Q1 2026, +53% in Q2 2026 on the same quarter a year earlier. Growth has been slowing, though from a high base.

Gross margin in the latest quarter was 88%, against 88% a year earlier, little changed. Operating margin moved from 76% to 78% over the same span. Over the latest four quarters it turned 66% of its revenue into operating cash flow.

Where it sits in the stack

AppLovin 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 8 by revenue and number 2 of 27 by revenue growth. Its gross margin of 88% compares with 78% 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 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, AppLovin grew +61% over the latest year versus +19% for the layer combined. It is taking share of the layer’s revenue.

What has to go right, and what could go wrong

What has to go right. Axon has to keep delivering better returns for advertisers than competing networks, and the expansion beyond mobile games into e-commerce has to work, so growth continues on a larger base.

What could go wrong. Changes in app-store or device privacy rules, a competitor’s better model, or advertisers seeing weaker returns would hit revenue directly, since there is little else in the business to offset them.

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 AppLovin’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 AppLovin, 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 individual customer represented 10% or more of the Company’s total revenue during the years ended December 31, 2025” 10-K, February 19, 2026

Commitments and backlog

• Backlog. AppLovin doesn’t report a comparable total of remaining performance obligations in its XBRL data.
• Purchase commitments. $703M of unconditional purchase obligations as of December 31, 2025 (10-K): what it has contracted to buy from its own suppliers.

What to watch

AppLovin’s next quarterly report will cover the quarter ending around September 29, 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 November 28, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• Revenue growth against the layer, now that the figures are the advertising business alone.
• Operating margin: the clearest read on whether model improvements keep turning into profit.
• Progress in e-commerce advertising, the market its 10-K names as its expansion.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from AppLovin’s SEC filings, latest period ended June 30, 2026. Other companies: all company pages.