OpenAI's Crossroads: The Identity Crisis and Industry Restructuring Behind the $14 Billion Loss Prediction

In the tech industry, nothing is more dramatic than a $500 billion unicorn predicting a $14 billion loss in two years. But that's the reality OpenAI is currently facing. However, through the complex discussions on X/Twitter, we see not only a company's financial difficulties, but also the fundamental restructuring that the entire generative AI industry is undergoing.

Structural Challenges Behind the Financial Figures

The news that OpenAI is expected to lose $14 billion in 2026 is not groundless. The reason this number is shocking is not only because of its absolute size, but also because it reveals the deep contradictions in the current AI business model.

SoftBank's recent financial report shows that its Vision Fund has obtained a quarterly income of $2.4 billion through OpenAI investment, which indirectly confirms the capital market's confidence in OpenAI. However, this confidence is built on an extremely fragile foundation. As one commentator pointed out: "Where does OpenAI's valuation come from today without GPT-4o?" This question hits the nail on the head.

More noteworthy is that OpenAI is simultaneously opening six or seven fronts—from consumer applications to enterprise services, from code generation to multimodal AI—but none of them have formed a decisive advantage. In business strategy, this is usually regarded as "economic suicide." If a company cannot build a moat in its core business and at the same time disperses resources in multiple fields, the result is often disastrous.

The Rise of Chinese Competitors and the Inevitability of Price Wars

"Chinese models are 20 times cheaper than their American counterparts, open source, and leading in usage." Although this observation may be exaggerated, it points to an undeniable trend: AI is undergoing a commoditization process similar to cloud computing and smartphones.

When technological barriers are lowered, the quality of open source alternatives improves, and price competition becomes inevitable. For companies like OpenAI, Anthropic, and Google, this means they must make a choice in two directions: either maintain premium capabilities through continuous technological innovation, or accept the reality of compressed profit margins and turn to scale competition.

At present, OpenAI seems to be trying to do both, but the effect is not ideal. The user backlash caused by the retirement of GPT-4o shows that even in the case of technological leadership, user loyalty is an extremely fragile asset.

GPT-4o Incident: The Rupture of User Trust and the Complexity of Emotional Connection

OpenAI's decision to retire the GPT-4o model has triggered a strong backlash in the user community. The importance of this event lies not in the technology itself, but in the fact that it reveals a new dimension of AI products: emotional connection.

The Wall Street Journal reported that users have developed an "emotional attachment" to ChatGPT, while Business Insider mentioned criticisms such as "excessive flattery" and "psychological delusion." These descriptions seem contradictory, but they actually point to the same problem: when an AI system is advanced enough, its relationship with humans is no longer a simple tool-user relationship, but a more complex, quasi-social interaction.

From a strategic point of view, OpenAI's handling of this issue exposed its "identity crisis." On the one hand, the company is trying to show technological progress through new products such as GPT-5.2; on the other hand, users feel "betrayed" and "forgotten." As one commentator said: "Completely offending the consumer end, destroying the most precious foundation core assets, destroying user loyalty" - the cumulative effect of these behaviors is far more destructive than any single technical decision.

The Evolution of Organizational Mission: From Non-profit to "Just Another Big Tech Company"

OpenAI's mission statement changes are the most telling. The company quietly removed wording such as "safety" and "no financial motivation," and acquired the founder of OpenClaw. These moves have been interpreted by critics as a sign of "just another big tech company."

Elon Musk's criticism, although personal, does touch on a core issue: "Open in OpenAI" originally represented open source and non-profit, which was a check and balance on the monopoly of large technology companies. When this mission is abandoned, OpenAI not only loses the moral high ground, but also loses an important part of its uniqueness.

This transformation is not unique to OpenAI, but a common challenge faced by the entire industry. When AI transforms from a research project to a commercial product, when safety considerations conflict with profit pressures, when open source ideals encounter the reality of a closed ecosystem, every company must make a choice. OpenAI's choice is obviously inclined to commercialization, but the long-term consequences of this choice are just beginning to appear.## Technical Optimism and Real Constraints

Sam Altman recently stated on X that building applications with Codex is "very fun" and even found that some feature ideas proposed by AI were "better than I thought." This technical optimism contrasts sharply with the real difficulties the company faces.

The number of Codex users tripled in six weeks, which is indeed impressive. But we need to ask: Is this growth sustainable? Can it be translated into real commercial value? In the field of AI programming tools, competition is intensifying, from GitHub Copilot to various emerging open-source alternatives, OpenAI is not the only player.

More importantly, technological progress is not always equal to commercial success. The comments of AI researcher Zoe Hitzig when she left OpenAI—"We don't understand the impact of AI on human psychology"—remind us that the social consequences of technological development are often unpredictable.

Restructuring the Industry Landscape: From Unipolar to Multipolar

Recent data shows that the AI industry is shifting from OpenAI's unipolar pattern to a multipolar pattern. Gemini surpassed ChatGPT in daily conversation volume for the first time, and Anthropic's daily active users increased by 11% after the Super Bowl ad—these are not accidental phenomena, but signs of industry maturity.

Interestingly, the reason Anthropic's ad went viral was precisely because it mocked OpenAI's practice of introducing ads into AI. This competition is not only at the technical and commercial level, but also at the level of values and vision.

In this context, OpenAI's recent moves—including the release of its first open-source models gpt-oss-120b and gpt-oss-20b in five years—can be interpreted as a response to competitive pressure. But whether these measures are sufficient and whether it is too late remains an open question.

Outlook: The Next Stage of AI

Standing at the node of 2024, we can see that the AI industry is entering a new stage. The characteristics of this stage are not breakthroughs in a single technology, but competition in the ecosystem; not a race for computing power and parameter scale, but a comprehensive competition for user experience, security, and sustainable business models.

For OpenAI, the challenge is not just financial or technical, but existential. As one observer pointed out: "The problem isn't technology or money—it's an identity crisis." A company that has lost its original mission, is fighting on multiple fronts at the same time, and whose core products are causing user backlash needs more than just better technology, but a clearer strategic positioning.

The $14 billion loss prediction may ultimately prove to be exaggerated, but the warning it raises is real: in the rapidly changing field of AI, today's leaders can easily become tomorrow's laggards. Whether OpenAI can avoid this fate depends on whether it can strike a balance between commercial success and its original mission, technological progress and social responsibility, and short-term profits and long-term sustainability.This balance is not only about the fate of a single company, but also about the direction of the entire AI industry. When we look back at this moment, we may find that 2024 is not the peak of AI prosperity, but the beginning of its mature stage—a stage full of challenges, but also full of possibilities.