Agentic AI Era: Every Enterprise Needs AIDP

In the era of intelligent agents, AI will possess the ability to understand complex instructions and autonomously execute tasks in dynamic processes.

For enterprises, AI will upgrade from an assistant to an employee or "automation engine," handling various complex business tasks. This is expected to bring about a doubling or exponential increase in production efficiency, triggering a qualitative change and reshaping enterprise production processes. AI agents have become a crucial element that all enterprises must pay attention to and act upon immediately.

Whoever can quickly integrate AI agents deeply with business systems will seize the initiative, occupy a leading position in the industry, and consolidate and expand their market advantage.In the future, each enterprise will have two major types of agents coexisting in the long term: one Data Agent + N business agents for vertical scenarios.

 

The essence of a Data Agent is the ultimate form of AI-driven data analysis" applications. It provides every enterprise with a unified data portal, enabling unified data analysis of structured, unstructured, and semi-structured data; in-depth business research; intelligent recommendations; and decision-making suggestions. When an enterprise builds such a Data Agent using its own data, every employee can have a 24/7 online business-savvy data analysis and decision-making assistant, which will help enterprises quickly achieve large-scale application of AI productivity tools.

Business agents, on the other hand, are innovative applications tailored to specific business scenarios, integrating AI into concrete business processes. Examples include industrial quality inspection and real-time financial fraud prevention. Starting with specific business problems, they build sub-business agents targeting specific scenarios, combining business logic with large-scale models and enterprise data to improve efficiency and create value in these sub-business scenarios.

While large-scale models have begun to converge and computing platforms have been built to a considerable scale, there are still few companies that can truly transform model capabilities into stable, scalable agents. There are two key bottlenecks behind this: scenarios and data. AIDP (AI Data Platform) is the key to breaking this deadlock. In the era of Agentic AI, every company needs an AIDP.

• perception
  
• understanding
  
• planning
  
• execution
  
• feedback
  
• collaboration
  

These capabilities rely on the coordinated efforts of four key technological components, none of which can be omitted:

1. Body: Infrastructure platform, providing hardware capabilities such as computing power, storage, network, and power.
2. Brain: Large language model, providing natural language understanding, logical reasoning and generation capabilities.
3. Physical components: Agent framework, tool invocation and API management, capability expansion.
4. Blood: A knowledge production line that can be directly accessed by AI from enterprise data, including datasets (data collection and preprocessing), corpora (text data for training large models), knowledge bases (enterprise-specific data and industry data), short-term memory (for storing the context of the current task), and long-term memory (for storing historical task experience and personalized data).

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