What happened in this episode?
AppLovin CEO Adam Foroughi outlines how the company positions itself as an advertising platform embedded in the mobile gaming ecosystem, which he estimates at roughly $50bn in annual ad spend. He says AppLovin previously disclosed $11bn of yearly spend on its own platform and claims the business has grown about 60% year-on-year since, implying a run-rate around $20bn.
Foroughi argues that advertising systems were an early, profitable proving ground for machine learning (“ML 1.0”), and describes AppLovin’s shift from regression models to deep learning (“ML 2.0”) as a major driver of improved ad performance. He distinguishes between “bottom-of-funnel” search ads—where he expects large language model interfaces to compete directly with Google’s search business—and “discovery” advertising, which he says creates new demand by showing users products they were not actively seeking.
On capital markets, Foroughi recounts AppLovin’s post-IPO volatility: he says the firm’s market capitalisation fell to about $3.8bn in 2022 despite generating roughly $1bn in EBITDA that year. He says the company responded by reducing investor engagement and launching aggressive buybacks, repurchasing about $6bn of stock and retiring 20–25% of shares. He also describes internal culture measures during the drawdown, including performance-based equity awards.
He addresses privacy regulation in broad terms, arguing that clearer rules help technology companies adapt, while maintaining consumers prefer relevant ads. He also says AppLovin bought and later sold game studios, describing the acquisitions as a way to obtain training data for early models.
