AppLovin & Its AI: A Lesson in Accuracy | Robinson+Cole Data Privacy + Security Insider
Last week, we explored a recent data breach class action and the litigation risk of such lawsuits. Companies need to be aware of litigation risk not only arising from data breaches, but also from shareholder class actions related to privacy concerns.
On March 5, 2025, a class action securities lawsuit was filed against AppLovin Corporation and its Chief Executive Officer and Chief Financial Officer (collectively, the defendants). AppLovin is a mobile advertising technology business that operates a software-based platform connecting mobile game developers to new users. AppLovin offers a software platform and an app. In the lawsuit, the plaintiff alleges that the defendants misled investors regarding AppLovin’s artificial intelligence (AI)-powered digital ad platform, AXON.
According to the complaint, the defendants made material representations through press releases and statements on earnings calls about how an upgrade to AppLovin’s AXON AI platform would provide improvements over the platform’s earlier version. The complaint further alleged that the defendants made numerous statements indicating that AppLovin’s financial growth in 2023 and 2024 was driven by improvements to the AXON technology. The defendants reportedly stated that AppLovin’s increase in net revenue per installation of the mobile app and the volume of installations was a result of the improved AXON technology.
The complaint further states that on, February 25, 2025, two short seller reports were published that linked AppLovin’s digital ad platform growth not to AXON, but to exploitative app permissions that carried out “backdoor” installations without users noticing. According to the reports, AppLovin used a code that purportedly allowed it to bind to consumers’ permissions for AppHub, Android’s centralized Google repository where app developers can upload and distribute their apps. The complaint claims that by attaching to AppHub’s one-click direct installations as its own, AppLovin directly downloaded apps onto consumers’ phones without their knowledge.
The research reports also state that AppLovin was reverse-engineering advertising data from Meta platforms and using manipulative practices, such as having ads click on themselves and forcing shadow downloads, to inflate its installation and profit figures. One of the research reports states that AppLovin was “intentionally vague about how its AI technology actually works,” and that the company used its upgraded AXON technology as a “smokescreen to hide the true drivers of its mobile gaming and e-commerce initiatives, neither of which have much to do with AI.” The reports further assert that the company’s “recent success in mobile gaming stems from the systematic exploitation of app permissions that enable advertisements themselves to force-feed silent, backdoor app installations directly onto users’ phones.” The complaint details the findings from the reports and alleges that AppLovin’s misrepresentations led to artificially inflated stock prices, which materially declined because of the research report findings.
On a company blog post in response to the research reports, the CEO wrote that “every download [of AppLovin] results from an explicit user choice—whether via the App Store or our Direct Download experience.”
As organizations begin integrating AI into their operations, they should be cautious in making representations regarding AI as a profitability driver. Executive leaders responsible for issuing press releases and leading earnings calls relating to a company’s technology practices should also understand how these technologies function and ensure that any statements they make are accurate. Whether such allegations are true or not, litigation around materially false representations can prove costly to an organization, both from a financial and reputation perspective.
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