Summary of Key Points
The emergence of AI (generative and agent-based technologies) is revolutionizing the role of government websites: from being mere information portals for humans to serving intelligent agents such as large-scale model assistants, digital civil servants, and corporate AI secretaries. This transformation shifts the focus from creating visually appealing and user-friendly web pages to ensuring that the content can be understood, accessed, and utilized by machines. The value, design logic, architecture, methods of handling affairs, and operational standards of government websites are all undergoing significant changes. The emphasis is no longer on how the website looks or functions for humans but on whether the information can be effectively processed by algorithms.
Detailed Analysis
1. Change in Service Targets: Intelligent Agents Take Center Stage
Previously, government websites were designed to facilitate human users in finding information. However, with the increasing use of AI assistants (e.g., asking ChatGPT about available startup subsidies), these intelligent agents have become the primary users of government services. In fact, the traffic generated by AI on government websites has surpassed that of human visitors! Therefore, the main service targets will be intelligent agents, just as restaurants no longer only serve customers but also robots that help with orders.
For example, if a business owner wants to know the requirements for a low-altitude economy project, they would previously have to navigate through various sections on a government website (e.g., industrial policies, low-altitude economy, approval processes). With AI assistants, these tools can directly retrieve the necessary information and explain it in plain language. In this context, the ability of the website to enable quick and accurate information retrieval by AI is far more important than its aesthetic appeal.
2. Shift in Value Focus: From Visual Appeal to Machine-usable Knowledge
The traditional value of government websites was centered around information dissemination, so factors like easy-to-remember domain names, attractive page layouts, and clear categorization were crucial. Now, the focus has shifted to whether policies can be understood by machines, whether processes can be automatically executed, and whether data can be effectively analyzed.
For instance, a policy used to be presented as a lengthy article that was difficult for AI to process. Today, policies are broken down into structured sections (policy name, issuing authority, effective date, eligible recipients, application requirements, processing procedures) so that AI can easily extract and use the relevant information. The value of a website lies in its underlying algorithms and localized policy databases, similar to how libraries are evaluated based on the efficiency with which their books can be searched and organized by robots.
3. Reversal of Design Logic: From Click-based Navigation to Direct Questioning
Traditional government websites had navigation bars that required users to click through multiple levels (home page → primary categories → subcategories → content pages) to find information. AI, on the other hand, can directly ask questions without such a need. In the future, government websites may feature intelligent question-and-answer interfaces where users can simply ask questions (e.g., “What procedures are needed to open a café?”), and the website will provide immediate answers, with navigation elements becoming less visible.
This means that website design will focus more on organizing knowledge in a way that is useful for machines rather than on creating visually appealing user experiences. The use of colors and layouts to attract users will give way to logically structured modules that enable AI to make connections between different pieces of information (e.g., linking subsidy application requirements with the necessary procedures).
4. A Two-tier Structure: Separate Layers for Humans and Intelligent Agents
Government websites will have two main layers:
- Human Layer: Includes existing visual content (text, images, guides) to accommodate users who cannot use AI (e.g., elderly people).
- Agent Layer: Contains data in a format that machines can understand. The same policy might be presented as an article for humans and as structured information (policy name, effective date, target audience, etc.) for intelligent agents. These pieces of information are connected through knowledge graphs (e.g., linking startup subsidies to relevant categories like “college students” and “application procedures”).
The role of websites will also change from simply publishing content to creating structured data that can be directly utilized by AI. This is similar to how writing essays is now broken down into smaller components (words, sentences, paragraphs) with clear relationships so that AI can easily combine them.
5. Upgraded Methods of Handling Affairs: From Guides to Intelligent Services
Guides on government websites used to be static documents that users had to read and fill out manually. In the future, these will evolve into intelligent services that can be directly accessed by AI (similar to smartphone apps). For example, an AI service for company relocation would automatically match relevant policies, generate application forms, handle the submission process, and track progress.
The operational focus will shift from optimizing website visibility (e.g., through SEO) to ensuring that AI can effectively understand user queries and apply policies accurately. Developers from the community could create useful services, which, after government review, could be promoted on the website. This approach would likely result in higher-quality and more diverse services than those developed in-house.
In Conclusion
In the AI era, government websites will no longer be mere information displays but intelligent engines that enable machines to efficiently access and utilize government resources, thereby enhancing efficiency in governance and decision-making. This represents a complete shift from content management to knowledge management.