Applovin's Q2 Earnings Surge 164% on AI-Driven Revenue Growth

Applovin, a leading player in the "AI+digital advertising" sector, has reported impressive financial results for the second quarter of its 2025 fiscal year. The company's performance was driven by its AI advertising engine model, AXON, which significantly contributed to its overall success. Applovin's actual earnings and revenue projections for the third quarter exceeded analysts' expectations, further solidifying its position in the market.

Applovin's adjusted earnings per share for the quarter ending June 30 were $2.39, surpassing the average analyst estimate of $2.32. Under the Generally Accepted Accounting Principles (GAAP), the company's earnings per share were $2.28, also exceeding the $1.98 average estimate. The company's net income for the second quarter, calculated under GAAP, reached $820 million, marking a 164% increase. Additionally, Applovin's total revenue for the quarter was $1.26 billion, surpassing the average analyst estimate of $1.22 billion, and representing a 17% year-over-year growth. Excluding the company's sold gaming business, Applovin's advertising revenue grew by 77% year-over-year. The company's adjusted EBITDA for the second quarter was $1.018 billion, a 99% year-over-year increase.

Looking ahead, Applovin expects third-quarter revenue to be between $1.32 billion and $1.34 billion, with the midpoint of this range exceeding the average analyst estimate of $1.31 billion. At the end of the second quarter, the company sold its mobile gaming business to Tripledot Studios for a total value of $400 million. This transaction allowed Applovin to focus on its core business, enabling it to concentrate on growth opportunities that will shape the company's future.

Applovin has successfully integrated generative AI and deep machine learning into its advertising technology. The company's AXON 2.0 engine, combined with MAX/AppDiscovery, creates a closed loop from ad buying to monetization. This has driven a 71% year-over-year increase in ad revenue for the first quarter of 2025, accounting for 78% of total revenue. Applovin's data network effect and economies of scale have not only increased eCPM and ROI but also exponentially expanded EBITDA.

Applovin's AXON 2.0 engine, powered by deep learning and reinforcement learning, uses real-time bidding to continuously optimize and convert large amounts of first-party and third-party signals into precise targeting capabilities. This is the direct driver of the company's rapid revenue and profit growth. AXON, which initially focused on mobile game user acquisition, now covers high-growth verticals such as e-commerce, fintech, and CTV. Applovin has become a leader in the "AI+digital advertising" sector by providing efficient programmatic ad placement in the mobile and CTV domains using its proprietary AXON AI algorithm platform.

The "super bull market" for AI applications is far from over. Before Applovin's earnings release, a major international bank highlighted that in a high market environment with AI concept speculation, Applovin possesses a rare business performance attribute within the broader AI concept sector, making it a worthy investment. The bank listed Applovin as a top pick for the earnings season, with a "buy" rating.

The bank's latest SMID-Cap internet preview report identified "AI+digital advertising" as the most certain super track in the stock market. The report's overall tone was "neutral to slightly positive," emphasizing Applovin and The Trade Desk as the top picks for the earnings season. The bank's optimism for these two AI application software leaders is based on their early realization of AI operational efficiency gains through next-generation ad placement algorithms and generative AI creativity, with significant potential for earnings upgrades and valuation increases.

Since the global popularity of ChatGPT in 2023, the integration of AI in the digital advertising sector has become an unstoppable trend. Industry giants Google and Meta have rapidly incorporated generative AI technology into their advertising systems, innovating in areas such as ad placement optimization and content presentation. Google has embedded machine learning algorithms in its ad network and cloud services to enhance placement efficiency, while Meta has used AI to improve ad placement returns and explore generative AI for content creation to boost user engagement and ad diversity.

The structural impact of AI integration is already evident. On one hand, AI enhances the precision and conversion effectiveness of digital ad placement, driving higher ROI for advertisers. On the other hand, AI-generated content and answers may divert some traffic, necessitating a reassessment of traditional ad inventory value. For instance, the frequency of ad displays based on Google's search patterns has increased, but click-through rates have decreased.

This year, AI application software providers such as C3.ai, Applovin, and Palantir have reported strong financial results and future projections, indicating robust demand for AI software applications that enhance operational efficiency. As global tech stock investment trends focus on both AI infrastructure and software applications, companies like Applovin, The Trade Desk, Duolingo, and Palantir are seeing significant valuation support. In the future, AI applications that cover both B2B and B2C sectors, as well as AI entities that could significantly boost human productivity, are expected to experience explosive growth. This is why global funds have recently flowed into software stocks.

Currently, the development direction of AI application software is focused on "generative AI applications" and AI entities that can autonomously execute complex tasks. AI entities are likely to be a major trend in AI applications by 2030, marking a shift from AI as an information assistant to a highly intelligent productivity tool. Enterprises' urgent need to improve efficiency and reduce operational costs is driving the widespread application of generative AI and AI entities. AI entities can automate repetitive tasks, perform large-scale data analysis, and provide real-time monitoring insights, enabling enterprises to make quick decisions and enhance operational efficiency. For individuals, AI entities can similarly boost learning and work efficiency, and participate in large-scale projects across various global industries, significantly accelerating project timelines.