On May 25, Microsoft released its fiscal third-quarter earnings report for fiscal year 2026. Total revenue reached $82.9 billion, a year-over-year increase of 18%. This figure itself is not surprising; what is surprising are two data points hidden within it.
First: AI business annualized revenue run rate exceeds $37 billion, up 123% year-over-year.
Second: Copilot paid seats reached 20 million.
Microsoft AI business annualized revenue run rate $37 billion · 123% year-over-year growth · Fiscal year 2026, third quarter
What does $37 billion mean? It already exceeds the annual revenue of many listed technology companies. And what does the 123% year-on-year growth rate indicate—a year ago, this figure was less than $17 billion, and now it has more than doubled.
Where does the money come from? Just look at RPO to find out.
The RPO (remaining performance obligations) metric is more compelling than current-quarter revenue. Microsoft's RPO reached $627 billion this quarter, up 99% year-over-year, nearly doubling.
RPO is the amount of revenue that customers have signed contracts for but have not yet recognized. The 99% growth indicates two things: first, large enterprises have a very strong willingness to sign AI contracts; second, these contracts are typically multi-year, large-scale deals. Azure cloud services grew 39%-40% at constant currency, with AI-related computing power demand being the main driver.
AI business annual revenue reached $37 billion, up 123% year-over-year. Remaining performance obligations (RPO) totaled $627 billion, up 99% year-over-year.
China Merchants Securities (Hong Kong) maintains a Buy rating with a target price of $616.4. Wedbush reiterates an Outperform rating with a target price of $575. The core logic of both institutions is consistent: Azure's AI demand has not yet peaked, and Copilot's enterprise penetration is still accelerating.
But here is a noteworthy signal: the biggest concern among institutions has shifted from "can it rise" to "how long can high growth be sustained". At the Evercore Global TMT Conference on June 2, analysts will likely press for answers on the return on capital expenditure.
On the same day, the domestic policy floodgates opened
On the same day Microsoft released its data (May 26), Xinhua Net published a lengthy article titled "AI Agents: More Than Just Chatting, They Can Really Get Work Done." The article contained a wealth of information, but the most interesting part was not the technical details—it was the timing.
In May, the Cyberspace Administration of China, the National Development and Reform Commission, and the Ministry of Industry and Information Technology jointly issued the "Implementation Opinions on the Standardized Application and Innovative Development of Intelligent Agents."
This is the first time at the national level to give an official definition of "intelligent agent": an intelligent system with autonomous perception, memory, decision-making, interaction, and execution capabilities, which is an important form of artificial intelligence products and services.
The document lists 19 typical application scenarios, covering industries such as manufacturing, finance, and government affairs, requiring the establishment of full-chain safety norms. In other words, previously, enterprises using intelligent agents were in a "gray area"—usable, but without rules. Now the rules are here.
In a recent public speech, Robin Li stated: "For the first time, the protagonist of AI is not the model, but the application." He proposed replacing DAU with DAA (Daily Active Agents) as a new metric for measuring the platform ecosystem — that is, how many agents are working for humans and delivering results.
This statement is particularly interesting when viewed against the backdrop of Microsoft's $37 billion. Essentially, the money Microsoft earns comes from companies paying for "AI that can work." Behind each of Copilot's 20 million paid seats is an enterprise user using AI to perform actual work tasks.
Three signals worth noting
Reading Microsoft's financial report together with China's domestic intelligent agent policies reveals several trends:
First, enterprise AI procurement is shifting from "testing the waters" to "budgeting." Microsoft's RPO has nearly doubled, indicating that companies are signing long-term contracts rather than one-time pilot projects. AI budgets are beginning to enter annual IT spending plans, much like cloud services and office software.
其次，“执行能力”取代“模型参数”成为竞争焦点。新华社的报道反复强调一个词——“行动AI”。百度、阿里巴巴、腾讯和字节跳动都在推广自己的Agent平台。Kimi帮助证券公司将研究报告初稿的撰写时间从2-3天压缩到2-3小时。千问×淘宝秒杀实现了“一键下单”+自动劝阻不合理购买。这些不是聊天机器人，而是直接介入业务流程的执行者。
Third, security boundaries have become a hard constraint.The implementation opinions issued by the three departments specifically address security governance. The 360 Artificial Intelligence Security Research Institute points out that risks are shifting from "generation risks" to "execution risks"—AI is no longer just saying the wrong thing, but may also autonomously perform out-of-bounds operations without human supervision. Alibaba's Tongyi Qianwen has launched a "citation" feature that automatically highlights sources with unclear information in red, while DP Technology's scientific research agents verify key conclusions through reproducible computation. These are all efforts to install "safety valves" for intelligent agents.
What this means for CIOs and digital leaders
If you are planning your company's AI strategy, here are a few practical suggestions:
- Stop just doing PoCs. Microsoft's data proves that enterprises that truly generate value have already entered the stage of large-scale deployment. If your AI project is still stuck in "selection and testing," you may need to pick up the pace in the second half of 2026.
- Focus on the security framework of intelligent agents. Domestic policies have begun to regulate the security boundaries of intelligent agents, and when purchasing, the supplier's security governance capabilities should be included in the evaluation criteria—not "whether the function exists," but "how to handle the fallout if something goes wrong."
- Re-examining the AI budget structure.Token costs are becoming ongoing operational expenses (the three major telecom operators are already selling token packages), a cost model completely different from traditional software licensing fees. It is recommended to set up a separate ledger.
The $37 billion figure is impressive, but for most Chinese companies, what may be more instructive is not how much Microsoft earned, but the customers behind it—why they are willing to sign multi-year contracts, and what kind of business value these contracts ultimately deliver.
References: Microsoft FY2026 Q3 Financial Report / Xinhua News Agency report on May 26 / "Implementation Opinions on the Standardized Application and Innovative Development of Intelligent Agents"
