Layout | Xiaoxi

It came as a surprise when WPS, a well-known software in China, found itself embroiled in a public outcry over "betraying users."

In late June, the topic of "feeling betrayed by WPS" suddenly surged on social media. Accusations ranged from "secretly accessing users' local files for AI training data" to complaints about the "unsightly necessity of paying for AI membership and additional features even after subscribing to a premium membership," fueling intense discussions. Despite multiple official responses and clarifications from WPS, the controversy proved difficult to quell.

▲ Note: Image sourced from Weibo

The eruption of this trust crisis seemed to have left WPS in a state of panic. However, upon closer inspection of the root cause, it becomes evident that all crises may stem from the rise of AI. This echoes the adage, "Those who disrupt you are often not your direct competitors."

As versatile large models like Doubao and Kimi begin to reshape productivity with their "free-for-all" approach, traditional applications like WPS, which once thrived on feature accumulation and path dependence for easy profits, are now facing an unprecedented survival challenge.

| National Software Faces an Existential Crisis |

For a long time, WPS has held a unique position in the Chinese software market, serving as both office software and a carrier of certain cultural sentiments.

From the 1980s to the present, the heroic narrative of WPS founder Qiu Bojun single-handedly writing tens of thousands of lines of code and stubbornly resisting Microsoft Office alongside Lei Jun, coupled with the strategy of providing basic features for free to individual users, has helped WPS amass a vast market share.

In the subconscious of many, WPS has always been perceived as the "conscientious, people-friendly, and understanding" "family member."

However, when companies enter the capital market and face immense pressure for revenue growth and profit realization, "sentiment" becomes a heavy burden. WPS's increasingly aggressive commercialization strategies have become the trigger for its reputation collapse.

In the past, users believed that purchasing a "VIP" membership would grant them access to all features. However, WPS has gradually evolved into offering multiple paid tiers such as "Membership," "Super Membership," "Super Membership Pro," and later "AI Membership." The nested "Matryoshka doll-style" pricing model frequently confronts users with paywalls when using features like PDF conversion and document watermark removal, forcing them to make repeated purchases.

▲ Note: Image sourced from WPS

To maximize the residual value of free users, ads have also started to randomly appear throughout documents, in startup pop-ups, bottom-right corner floaters, and even embedded within documents. Many users joke that "compared to office software, WPS's page now resembles a billboard."

The once-seamless office experience has been fragmented by ubiquitous paid prompts and ad pop-ups, coupled with increasingly bloated memory usage. Various commercialization operations that erode goodwill have left consumers "suffering from WPS for a long time."

If no better alternatives had emerged, users might have continued to tolerate these experience flaws. However, the advent of generative AI has easily broken this passive balance, impacting WPS's user base with unprecedented intensity.

In the past, the core barrier of office software lay in layout and format compatibility. Whether users were writing summaries, creating tables, or designing PPTs, they had to first open a local software, familiarize themselves with its complex menu bar, and slowly fill in a blank document. This was a typical "tool-oriented" process, where the tool only provided layout capabilities and a carrier for content, which had to be produced from scratch by the human brain.

However, generative AI models like ByteDance's Doubao and Yuezhi Anmian's Kimi have transformed the process into a "result-oriented" one. Users only need to input a simple instruction in Doubao's chatbox, and AI can generate a beautifully formatted, logically clear final document in just a few seconds for free.

It's important to note that among WPS's hundreds of millions of active users, only a handful truly need to use macro codes, complex functions, or engage in professional template design. The core needs of the vast majority of users are simply to write weekly reports, apply templates, and perform simple data summaries.

For these users, the emergence of large models has largely undermined their need for professional layout software like WPS. Since they can obtain finished products for free and with zero门槛 (threshold) through natural language conversations, why endure WPS's bloated startup speed, annoying ad ecosystem, and even spend tens of yuan on a monthly subscription?

The dimensionality reduction strike brought by AI has instantly breached the defensive moat of such traditional applications.

| AI Reshuffles the Deck, Traditional Applications Fall One by One |

WPS is not the only anxious traditional application. If we zoom out to the entire mobile internet application ecosystem, we will find a spectacular "great purge" underway. Traditional applications lacking deep industrial barriers, relying solely on "single functions" for success, or profiting from information gaps, are all facing compressed survival spaces.

In the early days of the internet, a large number of national-level applications that relied on vertical pain points and became popular were born. Their functions were mostly specialized: users used Software A for photo editing, Software B for translation, and Software C for recording; their business models were also highly similar, usually acquiring users with free basic features and then locking advanced features behind paywalls.

However, in the era of large models, versatility has become the core product attribute. Excellent underlying large models inherently possess cross-modal understanding and generation capabilities. They can not only write articles, understand and edit pictures but also are proficient in multiple languages and can process ultra-long audio. This means that general-purpose large models are launching indiscriminate attacks on vertical applications in all directions as "super individuals."

Meitu XiuXiu's defensive moat was built on lowering the barrier to using Photoshop and a vast library of filters. For over a decade, it has almost monopolized the minds of the general public for mobile photo editing, with users accustomed to manually adjusting contrast, smoothing skin, reshaping bodies, or purchasing "film filters" for a fee.

But today, with the proliferation of Midjourney, Stable Diffusion, and various domestic AI image generation tools, image processing has entered the generative era. Users no longer need to manually edit photos; they can simply send their photos to AI with instructions like "expand the image to 16:9 and fill in the surrounding environment" to achieve the desired photo effect.

▲ Note: Image sourced from AI

AI image expansion, partial redrawing, erasure, and one-click generation functions not only deliver stunning results but are often free or low-cost due to intense competition among large model vendors for users. Even the "filter library" painstakingly built by tool software like Meitu XiuXiu over the years has become vulnerable in the face of AI's generative capabilities.

Similar embarrassments are also unfolding in the traditional translation dictionary and audio transcription sectors. In the past, audio transcription apps often charged by duration, with an hour-long meeting transcription costing tens of yuan. Traditional translation software also required paid premium memberships for accurate translations of large paragraphs or professional literature.

But now, with large models like Kimi supporting ultra-long contexts of 2 million words, users can simply drag and drop hour-long meeting audio files or entire English original PDFs into the chatbox, and AI can quickly and accurately transcribe and translate them, even directly completing meeting minutes and summarizing key points.

Not to mention that traditional translation software can only provide word-for-word machine translations, often resulting in incoherent text, while large models can understand context, mimic specific writing styles based on user instructions, and perform "faithful, expressive, and elegant" customized rewrites combining industry knowledge.

After Apple introduced smartphones represented by the iPhone, it relied on the perfect fusion of communication, computing, photography, and music playback functions to turn MP3 players, compact digital cameras, walkmans, and calculators into relics of a bygone era overnight.

History always repeats itself in a striking manner. In today's "everything can be AI" era, large models resemble the "iPhone" of the new era, while traditional applications like WPS, Meitu, and translation software are becoming the "MP3s" that are gradually fading away.

| Marching into AI: "Betraying" Users is Easy, but Self-Redemption is Hard |

Traditional applications have not remained idle in the face of this wave of impact. Now, when you open a mobile app store, you will find that almost all established software are frantically adding the "AI" suffix to their names. WPS has launched "WPS AI," Meitu has introduced "Meitu Design Studio," and dictionary and recording software have also rolled out "AI Assistants."

Can this "if you can't beat them, join them" self-rescue initiative truly reverse their decline?

It's important to understand that developing a foundational large model capable of competing with Doubao or Tongyi Qianwen requires top AI talent reserves, tens of thousands of top-tier GPU computing clusters, and hundreds of billions of yuan in funding. This is clearly beyond the capabilities of a traditional tool software company.

▲ Note: Image sourced from AI

Therefore, their so-called "joining AI" is mostly "skin-deep" or "API calling," meaning they incorporate "AI patches" into their old products by accessing interfaces from giants like Alibaba, ByteDance, and Baidu or leading open-source large models.

However, the drawbacks of the skin-deep strategy are also evident. On one hand, the application's capability ceiling is forever constrained by the giant providing the API. When ByteDance prioritizes supplying its most advanced model capabilities to its own Doubao, tool software calling older API versions cannot compete head-on with the giants in terms of generation quality, logical reasoning, and response speed.

On the other hand, the reasoning costs of large models are exorbitant. If traditional tool software offers free AI functions, the massive API calling fees will quickly drag down their already fragile profit margins. If they charge for AI functions, with top products like Doubao and Kimi offering free or extremely low-cost subsidies, users have no reason to pay for "skin-deep and fee-based" products.

They are caught between technical costs and user expectations, but what's even more desperate than technical backwardness is the reshaping of the "interaction entrance."

Before the AI boom, users first needed to find the corresponding app entrance, click the icon, and enter its specific graphical user interface. Therefore, occupying users' desktops or home screens was the goal of all software. However, with the proliferation of generative AI, AI agents like Doubao and Kimi are becoming super brains and unified entrances frequently used by users, and the logic of human-computer interaction has also changed.

Users are accustomed to asking questions, searching for information, and generating copy in the same chatbox. Throughout this process, AI silently invokes various computing capabilities in the background, but for users, they never leave this chatting interface. When super large models can handle everything like a versatile secretary, users will have no incentive to "exit the current interface and search for specific tools among a pile of apps."

As these applications lose their qualification to be an "entrance," their survival space will be infinitely compressed. Ultimately, they will either exit the market or become API suppliers with extremely thin profit margins at the bottom of the large model ecosystem.

Technology advances relentlessly; no one can forever rely on the laurels of "sentiment." For traditional applications like WPS and Meitu that once brought convenience, "betraying" users may only require modifying a few lines of charging code. However, achieving true self-redemption in the era of large models is far from as simple as applying an "AI patch."

Image sourced from the internet. Rights reserved for the original author.