Claude Introduces Old Features as New Innovations

On April 10, Anthropic launched the public beta of Claude for Word, completing its integration into the Microsoft Office suite. Over six months, Claude has penetrated the Office ecosystem from Excel to PowerPoint and now Word.

The core feature emphasized by Anthropic is the ‘Track Changes’ mode. In their official demonstration, when opening an NDA contract, Claude provides editing suggestions in the right sidebar, presenting changes in Word’s native track changes format—original text struck through, new content marked as inserted, allowing users to accept or reject changes individually. Anthropic’s logic is straightforward: in industries like law, finance, and compliance, where audit trails are mandatory, track changes are not just an enhancement but a prerequisite.

This feature is indeed valuable. However, the question arises: is track changes an invention of AI?

No, it is a basic functionality present in both Word and WPS for over twenty years. Claude merely attaches AI outputs to this existing mechanism. In the Chinese market, WPS AI has provided a comparable track changes experience since integrating large models in 2023. When users request WPS AI to modify text, changes are also displayed in track changes format, allowing users to review, accept, or reject each modification. By the end of 2025, WPS AI’s domestic monthly active users exceeded 80.13 million, a 307% year-on-year increase, with 42% being enterprise users. This substantial user base indicates that features like track changes are not just for demonstration but are actively used by millions daily, continuously validating their productivity tools. Feedback from high-frequency usage further optimizes WPS AI’s document editing capabilities as user numbers grow.

The difference lies in the narrative. Claude packages ’track changes’ as a selling point, while WPS AI treats it as a standard feature. This reflects two divergent product philosophies: overseas AI companies often use a ‘disruption’ narrative to repackage existing features as new inventions, while Chinese office software takes a more pragmatic approach, embedding AI capabilities into existing workflows without emphasizing ‘what AI does’, allowing users to use it naturally.

The Real Experience Gap in ‘Cross-Application Collaboration’

Another widely discussed feature of Claude for Word is cross-Office collaboration—Word, Excel, and PowerPoint share context, allowing data to be pulled from Excel into Word and then condensed into a PowerPoint presentation. Anthropic defines this as an ‘AI-native office experience’.

However, ‘shared context’ and ‘integrated experience’ are two different matters. Claude’s cross-application collaboration relies on APIs connecting three independent products. Users invoke Claude within Word, which then accesses Excel and manipulates PowerPoint through interfaces. This process involves multiple transitions, where file format compatibility, account permission switches, and network delays can create friction points. In Anthropic’s own demonstration, extracting data from Excel to generate text in Word took several seconds, occasionally resulting in format misalignment—this was still in an idealized demo environment.

WPS 365 follows a different path. Documents, spreadsheets, presentations, PDFs, mind maps, and flowcharts all exist under the same account system, eliminating the need for ‘cross-application’ use since they are inherently part of one application. Users can simply say, ‘Create a chart from this spreadsheet data and insert it into the document’, and AI automatically completes the format conversion and content insertion. Saying, ‘Condense this document into a 10-page PowerPoint’, allows AI to extract key points and generate slides automatically. There are no account switches, format compatibility issues, or confusion about ‘where this file is stored’.

The fundamental difference between the two approaches is that Claude’s solution is to ‘integrate AI into multiple products’, while WPS’s solution is to ’embed AI within one product’. Integration is achievable, but fusion requires deep control over the underlying architecture.

Command-Driven vs. Context-Aware

Claude for Word employs a typical command-driven interaction model: users open a sidebar and input commands (e.g., ‘Help me revise this contract’ or ‘Summarize this document’), and Claude executes and returns results. This method offers strong control, allowing users to understand each step they are taking.

In addition to command-driven capabilities, WPS AI also incorporates context-aware functionality. When a user opens a labor contract, WPS AI automatically recognizes the document type without requiring user input, prompting in the right panel, ‘Detected labor contract; risk review of clauses is available’. Upon clicking, AI highlights specific risk points such as ’excessive penalty clauses’, ‘overly broad non-compete clauses’, and ’trial period duration not compliant with labor laws’. When a financial report is opened, WPS AI automatically switches to data analysis mode, suggesting ‘detected abnormal fluctuations’ and ‘can generate trend comparison charts’.

This is not merely about ‘making AI smarter’. Context awareness relies on long-term accumulation of knowledge about Chinese office scenarios: the recognition of contract types is based on training with vast amounts of Chinese contract data, and understanding financial reports comes from adapting to domestic accounting standards and report formats. Claude possesses a certain level of contextual understanding in English scenarios, but it lacks sufficient high-quality training data and contextual knowledge to support equivalent levels of automatic recognition in local scenarios such as Chinese contracts, financial reports, and government documents.

Divergence in Product Philosophy

The comparison between Claude for Word and WPS AI reveals two clear product trajectories.

Anthropic’s route can be summarized as ‘AI + Office’: focusing on model capabilities, integrating AI as an additional layer into existing office products. Claude’s core competitive advantage lies in the model itself—its ability to better understand user intent and generate more accurate content. The advantage of this route is rapid model iteration and strong versatility, while the disadvantage is limited depth of understanding specific scenarios, constrained by the openness of underlying products.

WPS’s route is ‘AI in Office’: centering on office scenarios, allowing AI capabilities to naturally integrate into existing user workflows. WPS AI does not pursue ‘doing everything’ but focuses on high-frequency scenarios in Chinese office work—contract review, document drafting, data analysis, and PowerPoint generation. The advantage of this route is deep scenario understanding and low user learning costs, while the disadvantage is that model capabilities depend on external partners (such as MiniMax, Zhiyu, etc.), potentially lacking the general capabilities of Claude.

There are no absolute advantages or disadvantages between the two routes; it depends on user needs. For multinational enterprise users primarily using English, Claude for Word may be the better choice; for domestic government and enterprise users primarily using Chinese, WPS AI’s scenario adaptation clearly offers more practical value.

Claude’s entry into Word marks a significant event in the global AI office landscape. However, in the Chinese office market, the competitive dimension has never been solely about ‘whose model is smarter’. The value of office tools ultimately reflects users’ real work efficiency, which is not solely dependent on AI capabilities but also on AI’s understanding of your contract types, document formats, and collaboration habits. In this respect, the thirty years of accumulated scenario data from local office software creates a gap that Claude cannot bridge in the short term.