Where is the next AI trading? Morgan Stanley: Discovering Alpha from "AI Diffusion Rate"

Morgan Stanley stated that the diffusion rate of AI will continue to drive excess returns in 2025, and investors should continue to focus on AI Enabler/Adopters. The financial sector is expected to become a new leader in AI "rate change," with a preference for Adopters that have high pricing power. As AI agents become more widespread, AI software stocks may outperform semiconductor stocks.

AI Diffusion Rate Drives Excess Returns

Morgan Stanley analyst Edward Stanley's team stated in a research report on January 6 that since the launch of ChatGPT over two years ago, the diffusion of AI is still in its early stages, but the pace of expansion is accelerating. The utilization of AI by enterprises is gradually increasing, especially in non-technical industries.

The AI diffusion rate has driven excess returns in stocks. The latest survey shows that among over 3,700 global stocks covered by Morgan Stanley, the market capitalization of AI "Enabler/Adopter" stocks has grown by 85% since 2022, adding approximately $14 trillion.

Stocks reclassified as "Core to Thesis" have outperformed the S&P 500 index by 45% since the release of ChatGPT. The number of "Core to Thesis" stocks in non-technical industries has significantly increased, indicating that enterprises are gradually incorporating AI into their core business logic. Conversely, stocks downgraded to "Disrupted" or "Wildcard" have significantly underperformed the S&P 500 in the long term.

2025 Will Be a Key Year for AI Agents

Morgan Stanley believes that 2025 will be a key year for AI agents, and like previous technology cycles, the stock market is ready for AI software companies to take over from AI semiconductor companies.

AI agents, as the name suggests, empower software programs with agency, transforming interactions with algorithms from passive (chatbots responding to user prompts) to active. Similarly, it shifts from static systems operating within clearly defined rule sets to dynamic systems seeking the best solutions to ever-changing problems.

Gartner estimates that by 2028, 33% of enterprise software applications will include AI agents, which will allow 15% of daily work decisions to be made autonomously by AI. The software sector may outperform the semiconductor sector due to the proliferation of AI agents. Since the launch of ChatGPT, the excess returns of the semiconductor sector have fallen from 100% to 70%.

The AI diffusion rate in the financial sector is rapidly increasing

Morgan Stanley believes that the financial industry is currently the fastest-growing sector in AI development. If utility stocks in AI power trading were the focus of stock pickers in the past six months, financial stocks may see a similar shift by 2025.

The importance of AI to financial companies is gradually increasing. Morgan Stanley's survey shows that more and more financial companies are shifting their view of AI from "not important" to "moderately important." This shift reflects the accelerated adoption of artificial intelligence technology in the financial industry and its tremendous potential in enhancing operational efficiency, risk management, and customer service.

Morgan Stanley states that there are two types of stocks in the financial sector that investors should pay special attention to.

First, financial and payment stocks marked by analysts as having increased exposure to AI, which means that these stocks have received analyst recognition for their progress in applying artificial intelligence technology and may contain higher growth potential.

Second, financial stocks for which analysts have upgraded the importance rating of AI, indicating that these companies are making positive changes in their artificial intelligence strategic layout and are expected to achieve better market performance in the future.

Preferentially select AI adopters with high pricing power

Morgan Stanley also advises investors to focus on the critical differences in pricing power among AI adopters.

Analysts state that pricing power is one of the key factors in screening AI adopter stocks.

In the context of rapid AI development, companies with high pricing power can better translate the efficiency gains brought by artificial intelligence into actual profits, thereby gaining an advantage in market competition.

Past market performance has proven this point; since the release of ChatGPT, high pricing power adopters have consistently outperformed their low pricing power peers, demonstrating stronger profitability and market competitiveness.

Adopter companies with high pricing power can convert the efficiency gains brought by AI technology into sustainable profit growth. In industries with higher pricing power (such as finance, energy, and consumer goods), AI efficiency gains are better retained. In addition to pricing power, companies with high-quality data, platforms, and moats also have significant advantages.

Analysts indicate that high-quality data is the foundation for training artificial intelligence algorithms, enhancing the accuracy and effectiveness of models. Strong platforms help integrate resources, achieving economies of scale and synergies The moat can protect the company's competitive advantage, preventing competitors from easily imitating and eroding it. These factors work together to make the development of these companies in the field of artificial intelligence more robust and their investment value higher.

Risk Warning and Disclaimer

The market has risks, and investment should be cautious. This article does not constitute personal investment advice and does not take into account the specific investment goals, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article align with their specific circumstances. Investment based on this is at one's own risk