What Exactly Is an AI Agent?

If you want to order a coffee for delivery at home using a traditional mobile app, your process would likely look like this: open the food delivery app, search for "coffee" (or a specific brand), find a satisfactory store, select the type of coffee you want, choose whether to remove ice or reduce sugar, enter or select the delivery address, click "order," and then enter your password or use facial recognition to pay…

But if your phone is equipped with an AI Agent (AI智能体 or AI代理), you only need to say to your phone, "Help me order a coffee and deliver it home as soon as possible." Without any further action, it will automatically recognize your location, open the food delivery app, accurately guess your preferences for the coffee brand and type, and complete the payment for you…

The 2025 World Artificial Intelligence Conference (WAIC 2025) opened in Shanghai on July 26, where AI Agents became a hot topic among attendees. In fact, since large models began competing in real-world applications, AI Agents have been repeatedly mentioned. So, after hearing so much, what exactly is an AI Agent? And what stage has it reached in its development?

How Is It Different from Traditional Smart Assistants?
"You can think of it as an 'all-around secretary,'" explained Wan Weixing, head of AI product technology for Qualcomm China, in simple terms to China News Service's "Zhongxin Jingwei." He noted that the "all-around" nature of an AI Agent means it can not only help with simple vertical tasks but also handle complex tasks covering all aspects of life and work.

"AI Agents will make life and work simpler and better," Wan said. Users only need to say one sentence, and the Agent can automatically complete tasks, making work and life easier. Its perceptiveness and personalization truly achieve "thinking what you think."

According to a June research report by China Galaxy Securities, Morgan Stanley's in-depth report "AI Agents Knocking at the Door" mentioned that AI Agents are no longer just tools to assist humans but are increasingly becoming entities that execute tasks and make decisions, evolving from simple automation tools into "digital labor" with autonomous understanding, action, and learning capabilities. The report describes AI Agents as autonomous software that can perceive environments, plan tasks, call tools, and iterate flexibly.

An AI Agent is not just a simple application but a complete system. "To complete a seemingly simple task, an AI Agent often requires at least four steps," Wan explained, using "ordering coffee" as an example. When a user issues a voice command, the Agent first converts the instruction into text via speech-to-text; then, it calls a large model (the 'brain') to understand the intent; next, it searches personalized memory to learn which app the user prefers for ordering coffee, their favorite flavor, home address, etc.; finally, it queries a database to fill in missing information, generates prompts, and either calls the coffee-ordering software interface or clicks through the app to complete the transaction.

Wan noted that "simulated clicking" is currently one of the ways AI Agents operate. Simply put, the Agent mimics human clicks, but the user doesn’t need to do anything—just give the command. In this mode, the time taken depends on the number of steps, such as how many pages need to be navigated. "Current metrics show that a single step can now be completed in under 2 seconds."

Compared to traditional smart assistants that follow a "I speak, it replies" model, Wan sees AI Agents as more like "coordinating decision-makers." He explained that chatbots and voice assistants rely heavily on specific and clear instructions, handling single, well-defined tasks, with humans still making most decisions.

Under the "human-led, AI-assisted" task-solving model, AI only executes commands. However, AI Agents, acting like "personal assistants," change this paradigm—they solve complex problems for users rather than requiring step-by-step interaction. Wan stated that a true AI Agent should operate in an "AI-led, human-assisted" manner, where humans only need to assign tasks or verify results, leaving most of the work to machines and AI.