When agents enter enterprises, what matters is no longer being smarter, but being more capable of getting things done.

On April 21st, the "Cloud Intelligence Sharing Session · Let's Get to Work, AGENT!" jointly initiated by Baidu Smart Cloud, 36Kr, Jixin, Origin School, and Origin Alumni Association was held in Beijing. At the event site, a judgment that was repeatedly mentioned is that as the basic capabilities of models are gradually leveling off, enterprises' focus on Agents is shifting from "whether it can generate and converse" to "whether it can access systems, be embedded in processes, and deliver stable results."

The Agents in demos often break down tasks, adjust tools, and connect to systems, looking like "all-rounders." However, once they enter real business scenarios, they quickly encounter problems such as permission isolation, system fragmentation, complex processes, and lack of auditing. If they can't enter the workflow, obtain necessary permissions, or have a traceable process, even the smartest Agents will find it difficult to truly stay in the business chain.

This is also the direction that Baidu Smart Cloud emphasized at the site: The threshold for enterprise-level Agents is no longer just model capabilities, but how to complete tasks under the premise of controllability and auditability. The solution presented at the site is that the front end solves the problem of Agent access to business through model encapsulation, Agent sandboxes, Skill systems, and workflow engines. The back end solves the problems of whether enterprises dare to put Agents into the process and whether they can trace problems in case of issues through security governance in five dimensions: product, identity, intelligent agents, network, and data. According to the on-site disclosure, the relevant capabilities have currently served nearly 30,000 employees within Baidu, and nearly 3,000 Skills have been launched.

More specifically, this change has become clear in three types of scenarios: content, transactions, and collaboration.

The first is content. In the past, people paid more attention to the generation speed and the similarity of content. Now, the more crucial question is whether the content can enter the links of placement, distribution, and conversion. ZeroCutAI is moving AI video customization towards a service priced by tokens, trying to solve problems such as repeated modification of requirements, difficult cost accounting, and unclear delivery boundaries. Genra.ai focuses more on the relationship between content and business results. In its view, video creation is shifting from "generating pixels" to "generating profits." Cutto incorporates scriptwriting knowledge, shot language, and narrative methods into its products, transforming the aesthetic judgment of professional scriptwriters into capabilities that ordinary creators can also use. PallasAI sees the change more directly: When users start to hand over part of their screening and purchasing judgments to AI, brands in the future not only need to impress consumers but also learn to be understood and recommended by AI.

This means that the focus of competition for content Agents is shifting from "generation ability" to "delivery ability."

The second is transactions. Agents are no longer staying at the information processing level but are further entering links closer to transaction results, such as matching, production, and fulfillment. OpenJobs AI turns "finding people" into a People Layer, trying to create an end-to-end autonomous AI recruitment officer. Leewow connects product design, factory translation, production, and shipping, attempting to directly turn a sentence or a picture into a product that can be ordered.

One is organizing people, and the other is organizing goods, but the underlying logic is similar: Agents are moving from "helping you understand information" to "helping you make a business actually happen."

The third is the collaboration interface. Agents are no longer just chat boxes waiting for instructions but are becoming real entrances to undertake tasks. At the same time, they are also showing stronger group characteristics. AirJelly hopes to directly connect the fleeting intentions in chats to the task flow, moving the task entrance forward to high-frequency communication scenarios. EvoMap emphasizes the group nature of Agents. Instead of making a single Agent more versatile, it enables multiple Agents to collaborate, share experiences, and precipitate paths, turning a single processing into reusable group capabilities. Baidu's partner DuMate implements its capabilities at the desktop execution level. Through security sandboxes, permission applications, and full-process auditing, Agents can both undertake tasks and be managed.

The market is gradually giving up the imagination of "all-purpose assistants" and is willing to pay for Agents that truly connect the links. In the current situation where AI applications are entering the deep waters of the industry, what is truly scarce may no longer be models that can talk better but Agents that can complete tasks.

The following is the long picture of the golden quotes from the guests at this event: