US Stock AI Applications: Differentiation in Accelerated Implementation

Reviewing the market performance of AI Agent stocks in the US this year, divided into three phases based on the model equalization from January to mid-February and the tariff fluctuations in early April. The first two phases generally followed the industry β with similar rises and falls, while the third phase saw individual stock differentiation driven by the monetization process of AI.

Phase One (January to mid-February): At the end of 2024, AI application companies released better-than-expected performance, creating optimistic future expectations. Coupled with the paradigm shift in generative AI and Agent technology at the beginning of 2025, US Agent stocks generally recorded good performance during this phase.

Phase Two (mid-February to early April): During this phase, expectations and implementations of tariffs, along with the delayed interest rate cuts by the Federal Reserve, had a significant negative impact on industry risk appetite, leading to valuation losses for Agent stocks, which may have been a key reason for the widespread decline during this phase.

Phase Three (early April to present): The marginal impact of tariffs has decreased, and the ARR of industry startups has accelerated. Whether US Agent stocks can leverage AI for volume growth or price increases has become the key to differentiation in this phase. The time for AI startups to achieve ARR growth has significantly shortened; for example, Anthropic's annualized revenue growth from $0 to $1 billion, $1 billion to $2 billion, and $2 billion to $3 billion occurred in January, March, and February, respectively, showcasing rapid revenue-generating capabilities; AI website building tool Lovable reached $100 million ARR in just 8 months.

The outstanding stocks from the beginning of the year to now can be mainly divided into two categories, both related to AI empowerment through volume increase or price rise. One category is represented by PLTR, where the core logic for the stock price increase lies in AI products deeply empowering the main business (such as AI improving service efficiency or expanding high-value customer scenarios), directly driving rapid revenue growth. This characteristic is particularly pronounced in the toB sector due to the easier implementation of business scenarios. The other category is represented by Spotify, which optimizes product experience through AI (such as precise recommendations and personalized upgrades), providing user-recognized value support for price increases, thereby improving profit margins and becoming a significant driving force for stock price increases.

1. Palantir (AI Volume Growth: From the beginning of the year to August 11, stock price +141.5%): After launching the AIP platform in 2023, it entered a high growth period for order performance. Total revenue reached $1.004 billion in Q2 2025, a year-on-year increase of +48%.

2. Spotify (AI Price Increase: From the beginning of the year to August 11, stock price +54.1%): With the support of AI features, product price increases have driven improvements in ARPPU and profit margins quarter by quarter. Over the three years from 2023 to 2025, Spotify has raised product prices three times. In Q2 2025, Spotify achieved an operating profit of €406 million, a year-on-year increase of 53%; the operating profit margin reached 9.7%, an increase of 2.7 percentage points year-on-year.

3. Applovin (AI Volume Growth: From the beginning of the year to August 11, stock price +43.8%): Axon AI, based on value delivery, has driven significant growth in advertising revenue Since Q3 2023, Applovin's advertising business revenue has maintained a high growth rate of over 60%.

4. SAP (AI expansion: from the beginning of the year to August 11, stock price +17.7%): Business AI has become an important means of order fulfillment, driving rapid growth in cloud business. In Q2 2025, over half of SAP's cloud orders included AI use cases, achieving revenue of €9.027 billion, a year-on-year increase of 8.9%, with cloud revenue of €5.13 billion, a year-on-year increase of 28%.

Companies that performed poorly were dragged down by AI-related issues, failing to realize the expected value creation from AI:

1. Insufficient synergy between AI and core business, making it difficult to form a second growth curve (e.g., not converting into user or revenue increments);

2. Excessive early-stage AI investment raised costs, temporarily dragging down profit margins.

For example, Salesforce's Q1 FY, the platform cloud and data analytics segments, which are highly related to AI and Agentforce, performed strongly, with growth rates exceeding expectations by about 5 percentage points and 4 percentage points, and significantly accelerated compared to the previous quarter; however, traditional IT spending segments such as sales, customer service, and marketing saw a quarter-on-quarter slowdown in growth, all below expectations. In addition, profits may be affected by upfront AI investments, with quarter-on-quarter growth slowing. From the beginning of the year to August 11, its stock price has cumulatively fallen by 30.2%.

This article is authored by Chen Hanbo and Li Peijing, sourced from AI Shengfushou, original title: "US Stock AI Applications: Differentiation in Accelerated Implementation | China Post Artificial Intelligence"

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