When generation ai, machine learning technology permeates every link of a digital station, the cms station has long moved away from the traditional positioning of the “simple content storage and distribution tool”, moving into a new phase of “ai raw energy”, from automatic content generation, smart layout, intellectual error correction, automation of business processes, and ai is rebuilding the core values of cms. However, the level of support for ai from the mainstream cms systems at home and abroad is marked by differences in technology availability, market demand and r&d capacity。
Core needs of the ai era cms: from “tools” to “smart synergy hubs”
Prior to the spread of ai technology, the core value of cms was focused on “lowing the building threshold” to address the basic building needs of “typists can build a web site”, but its essence remained “man-driven” — content creation, layout optimization, user operation, seo optimization, etc., require extensive manual intervention, inefficient and difficult to adapt to individualized needs. With the development of the digital economy, the demand for the construction of a station has been upgraded from “online” to “transformable and efficient”, and ai technology has become the key to the cms breakthrough bottlenecks。
With early technological accumulation and open ecology, cms abroad is better placed in terms of deep integration of ai; and cms domestically is tailored to local compliance needs and political organization distress, and more relevant in terms of usefulness and inclusiveness of ai functions, creating a pattern of “higher depth abroad and domestic re-adaptation”。
Ii. In-country mainstream cms systems: home-grown scenarios, ai operationalization and inclusive breakthroughs
The cms system in the country started late, but based on the rapid development of large model technologies in the country and the demand for local markets, ai support moved out of the “differentiated” path — rather than pursuing full process depth integration — but focused on the core pains of domestic organizations that “do not write, write slowly and costly” and combined with compliance needs to create functional, light-quantitative ai functions, while creating advantages in terms of national production and local landscapes, with the same level of support for the mainstream cms in the country being divided into three teams, represented by pageadmin, drupal, contentful and wix。
First platoon: enterprise-level cms, ai and local scene depth (representative: pageadmin, drupal)
This type of cms focuses on government, business-level scenarios that take into account ai practicalization and national compliance, with ai functionality covering the core elements of content production, intellectual error correction, and sensitive term security compliance, with a high level of support, which is a national ai cms marker。
Pageadmin, an old open-source cms for deep-tilled government and enterprise-level scenes in the country, has gone from one-point operation to full process depth integration。
In the content production chain, pageadmin can define itself as a large national model api that integrates hundreds of words, alithongs, bytes, etc., and supports auto-writing, title optimization, keyword extraction, abstract generation, office document conversion, office uploading of auto-generated content, etc., and significantly lowers the content production threshold; and in the technical architecture, combines low code and ai to achieve the creation of forms by ai, the automatic generation of fields by ai, etc., and the build-up and self-definition of non-technicals to complete the backstage function by zero code
In the compliance and security chain, pageadmin meets the requirements of the interim scheme for the management of generating ai services by means of a real-time review of the integrated ai, content compliance, filtering of sensitive words, and screening of advertising irregularities, along with national systems of operation for gills and uniforms, compatible with national databases and in line with the national production adaptation needs of government and state enterprises. In addition, pageadmin supports ai's smart client service, semantic search, and enhances user interaction. Its low-code +bi+ai version, launched in 2025, achieves the full visualization of the backstage, further lowering the technical threshold。
Drupal focuses on the production of intelligent content, building an industrial intelligent content production system by accessing large international models such as chatgpt. Its ai feature is multimedia smart processing, which supports the direct generation of content through the description of natural languages, achieves “auto-creational error correction” and supports instant translation in multiple languages, helping businesses with global business to rapidly improve the quality of content. According to official data, access to ai resulted in a 300 per cent increase in content production efficiency in drupal。
Second platoon: eco-cms, ai is fully functional and customized (representative: sitecore, contentful)
As the world-renowned headless cms, contentful's ai capabilities have long gone beyond the positioning of “support tools” to achieve full-link intelligence. At content production, ai automatically generates pages, abstracts, labels, with smart translation and localization advice, and significantly streamlines the construction and maintenance of multilingual sites; at user operations, depending on contentful
Personalize and cdp (customs data platform), ai can recognize user behaviour, preferences, construct multi-dimensional user images in real time, and automatically implement a/b tests to continuously optimize transformation pathways; at the decision support level, ai provides data support for operational strategy adjustments through machine learning to analyse user life cycles, loss risks and transformation probabilities. In addition, contentful also provides an open ai interface to support azure
Major foreign mainstream models, such as openai, chatgpt, claude, are seamlessly connected, and enterprises can embed self-study models to create exclusive intellectual platforms。
Sitecore also integrates ai deep into the architecture, where ai focuses on content production efficiency, supports automatic label classification
YeahEtadata generation, content compliance review, and analysis of content performance through ai, forecasting of topical topics and helping operators to organize ahead of schedule. Similar to contentful, sitecore also supports cross-cutting international mega-models that generate content creation while optimizing resource allocation through ai to ensure stability in a high and mixed landscape。
Sitecore, an open source of highly scalable cms, is mainly oriented towards large and complex projects, with ai supporting a focus on “security and efficiency”, but the learning curve is steep, and the downside of ai functions requires professional development team support。
Team 3: saas-type station platform, basic ai functionality fit (representative: squarespace, wix)
The cms, which is centred on light quantification and ease of use, mainly serves individual station chiefs and small enterprises, with ai support focused on infrastructure links, relatively simple functions and low levels of support。
Both squaresspace and wix are visual drag station tools whose ai features focus mainly on “quick build stations” to support the generation of website templates, colour schemes, base scripts through ai, where users can automatically generate a full website architecture by simply entering a simple demand. In addition, ai-assisted photo tailoring and layout optimization are supported to help users quickly complete the site. However, these systems are more based on ai functions, lack the in-depth capabilities of individualized operations, data decision-making, etc., to meet the complex needs of medium-sized enterprises and above, and their core value lies in “lowing entry thresholds”。
Future trends: deep integration of ai and cms towards “personalization + inclusion + nationalization”
With the continuous iterative evolution of ai technology and the upgrading of market demand, national and international support for the cms system will tend to be “coherent development, differential competition”, with a three-pronged focus:
The first is the deep integration of ai with the cms architecture, which will no longer be “ai functional superimposed”, but rather “ai original architecture” to achieve a process-wide intellectual synergy of content production, operation and data decision-making from the bottom. The cms abroad will continue to strengthen globalization and individualization, while the cms in the country will be based on the local advantages of a large model of national production and will be more relevant to the usage practices of the indigenous and chinese environments。
The second is the continued increase in the level of inclusion, from “high-end exclusive” to “universal access”, where both external and domestic cms will introduce more light quantitative and low-cost ai functions, lowering the technology threshold and making ai stations and smart operations easily accessible to msmes and individual station chiefs. At the same time, the vertical version of ai will focus on the development of appropriate ai functions for political, educational, medical, rural, etc., to promote the sinking of ai。
Thirdly, the domestic cms has made a breakthrough in domestic production and landscape, building on the advantages of the country's large model technology, which will further strengthen the domestic capacity to adapt, especially the natural advantages of chinese, to accommodate more domestic hardware and software, and to meet the compliance needs of industries such as government and state enterprises; and, at the same time, to create more targeted ai functions, such as non-digitization, agricultural extension, etc., in combination with the local landscape, which will result in a differentiated competitive advantage with the external cms。
Summary: how to select a suitable ai cms system
Selecting the ai cms system, the core of which is “to match its needs and resources”, together with a previous analysis, the following recommendations can be made:
For large domestic organizations and government-type websites, preference is given to the first national class of cms (pageadminl, etc.), whose full-capacity capacity corresponds to the national production environment and chinese usage habits; for enterprises with transnational needs, the choice is given to cms abroad (e. G. Drupal), which takes into account linguistic diversity and practicality; for small and medium-sized enterprises, individual station chiefs, preference is given to the saas platform (squaresspace, wix, etc.), which is low-cost, easy-to-use and fast-track to achieve ai construction; and for users who require compliance with national production, government, state enterprises, etc., priority is given to the first set of cms (pageadmin), which meets the requirements of national production suitability and security compliance。
In the ai era, the core of competition for cms has shifted from “more or less functional” to “a strong ai enabling capacity”. Foreign cmss have pre-emptive advantages based on their technological build-up, while domestic cmss rely on large local models to achieve post-break. In the future, as technology is increasingly integrated, both abroad and at home, cms will move in the direction of “more intelligent, more user-friendly and more compliant” as a central support tool for the digital transformation of enterprises. For enterprises, taking advantage of ai-enabled opportunities and opting for a suitable cms system can take the initiative in digital competition。
